Modeling-Error-Driven Performance-Seeking Direct Adaptive Control
NASA Technical Reports Server (NTRS)
Kulkarni, Nilesh V.; Kaneshige, John; Krishnakumar, Kalmanje; Burken, John
2008-01-01
This paper presents a stable discrete-time adaptive law that targets modeling errors in a direct adaptive control framework. The update law was developed in our previous work for the adaptive disturbance rejection application. The approach is based on the philosophy that without modeling errors, the original control design has been tuned to achieve the desired performance. The adaptive control should, therefore, work towards getting this performance even in the face of modeling uncertainties/errors. In this work, the baseline controller uses dynamic inversion with proportional-integral augmentation. Dynamic inversion is carried out using the assumed system model. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to the dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. Contrary to the typical Lyapunov-based adaptive approaches that guarantee only stability, the current approach investigates conditions for stability as well as performance. A high-fidelity F-15 model is used to illustrate the overall approach.
NASA Astrophysics Data System (ADS)
Ulrich, Steve
This work addresses the direct adaptive trajectory tracking control problem associated with lightweight space robotic manipulators that exhibit elastic vibrations in their joints, and which are subject to parametric uncertainties and modeling errors. Unlike existing adaptive control methodologies, the proposed flexible-joint control techniques do not require identification of unknown parameters, or mathematical models of the system to be controlled. The direct adaptive controllers developed in this work are based on the model reference adaptive control approach, and manage modeling errors and parametric uncertainties by time-varying the controller gains using new adaptation mechanisms, thereby reducing the errors between an ideal model and the actual robot system. More specifically, new decentralized adaptation mechanisms derived from the simple adaptive control technique and fuzzy logic control theory are considered in this work. Numerical simulations compare the performance of the adaptive controllers with a nonadaptive and a conventional model-based controller, in the context of 12.6 m xx 12.6 m square trajectory tracking. To validate the robustness of the controllers to modeling errors, a new dynamics formulation that includes several nonlinear effects usually neglected in flexible-joint dynamics models is proposed. Results obtained with the adaptive methodologies demonstrate an increased robustness to both uncertainties in joint stiffness coefficients and dynamics modeling errors, as well as highly improved tracking performance compared with the nonadaptive and model-based strategies. Finally, this work considers the partial state feedback problem related to flexible-joint space robotic manipulators equipped only with sensors that provide noisy measurements of motor positions and velocities. An extended Kalman filter-based estimation strategy is developed to estimate all state variables in real-time. The state estimation filter is combined with an adaptive
Liu, Derong; Li, Hongliang; Wang, Ding
2015-06-01
In this paper, we establish error bounds of adaptive dynamic programming algorithms for solving undiscounted infinite-horizon optimal control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update equations of both value function and control policy. We utilize a new assumption instead of the contraction assumption in discounted optimal control problems. We establish the error bounds for approximate value iteration based on a new error condition. Furthermore, we also establish the error bounds for approximate policy iteration and approximate optimistic policy iteration algorithms. It is shown that the iterative approximate value function can converge to a finite neighborhood of the optimal value function under some conditions. To implement the developed algorithms, critic and action neural networks are used to approximate the value function and control policy, respectively. Finally, a simulation example is given to demonstrate the effectiveness of the developed algorithms. PMID:25751878
Chemachema, Mohamed
2012-12-01
A direct adaptive control algorithm, based on neural networks (NN) is presented for a class of single input single output (SISO) nonlinear systems. The proposed controller is implemented without a priori knowledge of the nonlinear systems; and only the output of the system is considered available for measurement. Contrary to the approaches available in the literature, in the proposed controller, the updating signal used in the adaptive laws is an estimate of the control error, which is directly related to the NN weights instead of the tracking error. A fuzzy inference system (FIS) is introduced to get an estimate of the control error. Without any additional control term to the NN adaptive controller, all the signals involved in the closed loop are proven to be exponentially bounded and hence the stability of the system. Simulation results demonstrate the effectiveness of the proposed approach. PMID:23037773
Design implementation and control of MRAS error dynamics. [Model-Reference Adaptive System
NASA Technical Reports Server (NTRS)
Colburn, B. K.; Boland, J. S., III
1974-01-01
Use is made of linearized error characteristic equation for model-reference adaptive systems to determine a parameter adjustment rule for obtaining time-invariant error dynamics. Theoretical justification of error stability is given and an illustrative example included to demonstrate the utility of the proposed technique.
NASA Astrophysics Data System (ADS)
Chowdhary, Girish; Mühlegg, Maximilian; Johnson, Eric
2014-08-01
In model reference adaptive control (MRAC) the modelling uncertainty is often assumed to be parameterised with time-invariant unknown ideal parameters. The convergence of parameters of the adaptive element to these ideal parameters is beneficial, as it guarantees exponential stability, and makes an online learned model of the system available. Most MRAC methods, however, require persistent excitation of the states to guarantee that the adaptive parameters converge to the ideal values. Enforcing PE may be resource intensive and often infeasible in practice. This paper presents theoretical analysis and illustrative examples of an adaptive control method that leverages the increasing ability to record and process data online by using specifically selected and online recorded data concurrently with instantaneous data for adaptation. It is shown that when the system uncertainty can be modelled as a combination of known nonlinear bases, simultaneous exponential tracking and parameter error convergence can be guaranteed if the system states are exciting over finite intervals such that rich data can be recorded online; PE is not required. Furthermore, the rate of convergence is directly proportional to the minimum singular value of the matrix containing online recorded data. Consequently, an online algorithm to record and forget data is presented and its effects on the resulting switched closed-loop dynamics are analysed. It is also shown that when radial basis function neural networks (NNs) are used as adaptive elements, the method guarantees exponential convergence of the NN parameters to a compact neighbourhood of their ideal values without requiring PE. Flight test results on a fixed-wing unmanned aerial vehicle demonstrate the effectiveness of the method.
Bio-inspired adaptive feedback error learning architecture for motor control.
Tolu, Silvia; Vanegas, Mauricio; Luque, Niceto R; Garrido, Jesús A; Ros, Eduardo
2012-10-01
This study proposes an adaptive control architecture based on an accurate regression method called Locally Weighted Projection Regression (LWPR) and on a bio-inspired module, such as a cerebellar-like engine. This hybrid architecture takes full advantage of the machine learning module (LWPR kernel) to abstract an optimized representation of the sensorimotor space while the cerebellar component integrates this to generate corrective terms in the framework of a control task. Furthermore, we illustrate how the use of a simple adaptive error feedback term allows to use the proposed architecture even in the absence of an accurate analytic reference model. The presented approach achieves an accurate control with low gain corrective terms (for compliant control schemes). We evaluate the contribution of the different components of the proposed scheme comparing the obtained performance with alternative approaches. Then, we show that the presented architecture can be used for accurate manipulation of different objects when their physical properties are not directly known by the controller. We evaluate how the scheme scales for simulated plants of high Degrees of Freedom (7-DOFs). PMID:22907270
NASA Astrophysics Data System (ADS)
Hirthe, E. M.; Graf, T.
2012-04-01
Fluid density variations occur due to changes in the solute concentration, temperature and pressure of groundwater. Examples are interaction between freshwater and seawater, radioactive waste disposal, groundwater contamination, and geothermal energy production. The physical coupling between flow and transport introduces non-linearity in the governing mathematical equations, such that solving variable-density flow problems typically requires very long computational time. Computational efficiency can be attained through the use of adaptive time-stepping schemes. The aim of this work is therefore to apply a non-iterative adaptive time-stepping scheme based on local truncation error in variable-density flow problems. That new scheme is implemented into the code of the HydroGeoSphere model (Therrien et al., 2011). The new time-stepping scheme is applied to the Elder (1967) and the Shikaze et al. (1998) problem of free convection in porous and fractured-porous media, respectively. Numerical simulations demonstrate that non-iterative time-stepping based on local truncation error control fully automates the time step size and efficiently limits the temporal discretization error to the user-defined tolerance. Results of the Elder problem show that the new time-stepping scheme presented here is significantly more efficient than uniform time-stepping when high accuracy is required. Results of the Shikaze problem reveal that the new scheme is considerably faster than conventional time-stepping where time step sizes are either constant or controlled by absolute head/concentration changes. Future research will focus on the application of the new time-stepping scheme to variable-density flow in complex real-world fractured-porous rock.
Padrão, Gonçalo; Penhune, Virginia; de Diego-Balaguer, Ruth; Marco-Pallares, Josep; Rodriguez-Fornells, Antoni
2014-10-15
The ability to detect and use information from errors is essential during the acquisition of new skills. There is now a wealth of evidence about the brain mechanisms involved in error processing. However, the extent to which those mechanisms are engaged during the acquisition of new motor skills remains elusive. Here we examined rhythm synchronization learning across 12 blocks of practice in musically naïve individuals and tracked changes in ERP signals associated with error-monitoring and error-awareness across distinct learning stages. Synchronization performance improved with practice, and performance improvements were accompanied by dynamic changes in ERP components related to error-monitoring and error-awareness. Early in learning, when performance was poor and the internal representations of the rhythms were weaker we observed a larger error-related negativity (ERN) following errors compared to later learning. The larger ERN during early learning likely results from greater conflict between competing motor responses, leading to greater engagement of medial-frontal conflict monitoring processes and attentional control. Later in learning, when performance had improved, we observed a smaller ERN accompanied by an enhancement of a centroparietal positive component resembling the P3. This centroparietal positive component was predictive of participant's performance accuracy, suggesting a relation between error saliency, error awareness and the consolidation of internal templates of the practiced rhythms. Moreover, we showed that during rhythm learning errors led to larger auditory evoked responses related to attention orientation which were triggered automatically and which were independent of the learning stage. The present study provides crucial new information about how the electrophysiological signatures related to error-monitoring and error-awareness change during the acquisition of new skills, extending previous work on error processing and cognitive
NASA Astrophysics Data System (ADS)
Zhang, Menghua; Ma, Xin; Rong, Xuewen; Tian, Xincheng; Li, Yibin
2016-08-01
In a practical application, overhead cranes are usually subjected to system parameter uncertainties, such as uncertain payload masses, cable lengths, frictions, and external disturbances, such as air resistance. Most existing crane control methods treat the payload swing as that of a single-pendulum. However, certain types of payloads and hoisting mechanisms result in double-pendulum dynamics. The double-pendulum effects will make most existing crane control methods fail to work normally. Therefore, an adaptive tracking controller for double-pendulum overhead cranes subject to parametric uncertainties and external disturbances is developed in this paper. The proposed adaptive tracking control method guarantees that the trolley tracking error is always within a prior set of boundary conditions and converges to zero rapidly. The asymptotic stability of the closed-loop system's equilibrium point is assured by Lyapunov techniques and Barbalat's Lemma. Simulation results show that the proposed adaptive tracking control method is robust with respect to system parametric uncertainties and external disturbances.
Zaafouri, Abderrahmen; Ben Regaya, Chiheb; Ben Azza, Hechmi; Châari, Abdelkader
2016-01-01
This paper presents a modified structure of the backstepping nonlinear control of the induction motor (IM) fitted with an adaptive backstepping speed observer. The control design is based on the backstepping technique complemented by the introduction of integral tracking errors action to improve its robustness. Unlike other research performed on backstepping control with integral action, the control law developed in this paper does not propose the increase of the number of system state so as not increase the complexity of differential equations resolution. The digital simulation and experimental results show the effectiveness of the proposed control compared to the conventional PI control. The results analysis shows the characteristic robustness of the adaptive control to disturbances of the load, the speed variation and low speed. PMID:26653141
Aircraft system modeling error and control error
NASA Technical Reports Server (NTRS)
Kulkarni, Nilesh V. (Inventor); Kaneshige, John T. (Inventor); Krishnakumar, Kalmanje S. (Inventor); Burken, John J. (Inventor)
2012-01-01
A method for modeling error-driven adaptive control of an aircraft. Normal aircraft plant dynamics is modeled, using an original plant description in which a controller responds to a tracking error e(k) to drive the component to a normal reference value according to an asymptote curve. Where the system senses that (1) at least one aircraft plant component is experiencing an excursion and (2) the return of this component value toward its reference value is not proceeding according to the expected controller characteristics, neural network (NN) modeling of aircraft plant operation may be changed. However, if (1) is satisfied but the error component is returning toward its reference value according to expected controller characteristics, the NN will continue to model operation of the aircraft plant according to an original description.
Wang, Fei-Yue; Jin, Ning; Liu, Derong; Wei, Qinglai
2011-01-01
In this paper, we study the finite-horizon optimal control problem for discrete-time nonlinear systems using the adaptive dynamic programming (ADP) approach. The idea is to use an iterative ADP algorithm to obtain the optimal control law which makes the performance index function close to the greatest lower bound of all performance indices within an ε-error bound. The optimal number of control steps can also be obtained by the proposed ADP algorithms. A convergence analysis of the proposed ADP algorithms in terms of performance index function and control policy is made. In order to facilitate the implementation of the iterative ADP algorithms, neural networks are used for approximating the performance index function, computing the optimal control policy, and modeling the nonlinear system. Finally, two simulation examples are employed to illustrate the applicability of the proposed method. PMID:20876014
NASA Astrophysics Data System (ADS)
Hirthe, Eugenia M.; Graf, Thomas
2012-12-01
The automatic non-iterative second-order time-stepping scheme based on the temporal truncation error proposed by Kavetski et al. [Kavetski D, Binning P, Sloan SW. Non-iterative time-stepping schemes with adaptive truncation error control for the solution of Richards equation. Water Resour Res 2002;38(10):1211, http://dx.doi.org/10.1029/2001WR000720.] is implemented into the code of the HydroGeoSphere model. This time-stepping scheme is applied for the first time to the low-Rayleigh-number thermal Elder problem of free convection in porous media [van Reeuwijk M, Mathias SA, Simmons CT, Ward JD. Insights from a pseudospectral approach to the Elder problem. Water Resour Res 2009;45:W04416, http://dx.doi.org/10.1029/2008WR007421.], and to the solutal [Shikaze SG, Sudicky EA, Schwartz FW. Density-dependent solute transport in discretely-fractured geological media: is prediction possible? J Contam Hydrol 1998;34:273-91] problem of free convection in fractured-porous media. Numerical simulations demonstrate that the proposed scheme efficiently limits the temporal truncation error to a user-defined tolerance by controlling the time-step size. The non-iterative second-order time-stepping scheme can be applied to (i) thermal and solutal variable-density flow problems, (ii) linear and non-linear density functions, and (iii) problems including porous and fractured-porous media.
Adaptive control for accelerators
Eaton, Lawrie E.; Jachim, Stephen P.; Natter, Eckard F.
1991-01-01
An adaptive feedforward control loop is provided to stabilize accelerator beam loading of the radio frequency field in an accelerator cavity during successive pulses of the beam into the cavity. A digital signal processor enables an adaptive algorithm to generate a feedforward error correcting signal functionally determined by the feedback error obtained by a beam pulse loading the cavity after the previous correcting signal was applied to the cavity. Each cavity feedforward correcting signal is successively stored in the digital processor and modified by the feedback error resulting from its application to generate the next feedforward error correcting signal. A feedforward error correcting signal is generated by the digital processor in advance of the beam pulse to enable a composite correcting signal and the beam pulse to arrive concurrently at the cavity.
Control by model error estimation
NASA Technical Reports Server (NTRS)
Likins, P. W.; Skelton, R. E.
1976-01-01
Modern control theory relies upon the fidelity of the mathematical model of the system. Truncated modes, external disturbances, and parameter errors in linear system models are corrected by augmenting to the original system of equations an 'error system' which is designed to approximate the effects of such model errors. A Chebyshev error system is developed for application to the Large Space Telescope (LST).
Stability and error estimation for Component Adaptive Grid methods
NASA Technical Reports Server (NTRS)
Oliger, Joseph; Zhu, Xiaolei
1994-01-01
Component adaptive grid (CAG) methods for solving hyperbolic partial differential equations (PDE's) are discussed in this paper. Applying recent stability results for a class of numerical methods on uniform grids. The convergence of these methods for linear problems on component adaptive grids is established here. Furthermore, the computational error can be estimated on CAG's using the stability results. Using these estimates, the error can be controlled on CAG's. Thus, the solution can be computed efficiently on CAG's within a given error tolerance. Computational results for time dependent linear problems in one and two space dimensions are presented.
The Pupillary Orienting Response Predicts Adaptive Behavioral Adjustment after Errors
Murphy, Peter R.; van Moort, Marianne L.; Nieuwenhuis, Sander
2016-01-01
Reaction time (RT) is commonly observed to slow down after an error. This post-error slowing (PES) has been thought to arise from the strategic adoption of a more cautious response mode following deployment of cognitive control. Recently, an alternative account has suggested that PES results from interference due to an error-evoked orienting response. We investigated whether error-related orienting may in fact be a pre-cursor to adaptive post-error behavioral adjustment when the orienting response resolves before subsequent trial onset. We measured pupil dilation, a prototypical measure of autonomic orienting, during performance of a choice RT task with long inter-stimulus intervals, and found that the trial-by-trial magnitude of the error-evoked pupil response positively predicted both PES magnitude and the likelihood that the following response would be correct. These combined findings suggest that the magnitude of the error-related orienting response predicts an adaptive change of response strategy following errors, and thereby promote a reconciliation of the orienting and adaptive control accounts of PES. PMID:27010472
Hybrid Adaptive Flight Control with Model Inversion Adaptation
NASA Technical Reports Server (NTRS)
Nguyen, Nhan
2011-01-01
This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.
Larson, Michael J; LeCheminant, James D; Carbine, Kaylie; Hill, Kyle R; Christenson, Edward; Masterson, Travis; LeCheminant, Rick
2015-01-01
An increasing trend in the workplace is for employees to walk on treadmills while working to attain known health benefits; however, the effect of walking on a treadmill during cognitive control and executive function tasks is not well known. We compared the cognitive control processes of conflict adaptation (i.e., congruency sequence effects-improved performance following high-conflict relative to low-conflict trials), post-error slowing (i.e., Rabbitt effect), and response inhibition during treadmill walking (1.5 mph) relative to sitting. Understanding the influence of treadmill desks on these cognitive processes may have implications for worker health and productivity. Sixty-nine individuals were randomized to either a sitting (n = 35) or treadmill-walking condition (n = 34). Groups did not differ in age or body mass index. All participants completed a computerized Eriksen flanker task and a response-inhibition go/no-go task in random order while either walking on a treadmill or seated. Response times (RTs) and accuracy were analyzed separately for each task using mixed model analysis of variance. Separate ANOVAs for RTs and accuracy showed the expected conflict adaptation effects, post-error slowing, and response inhibition effects when collapsed across sitting and treadmill groups (all Fs > 78.77, Ps < 0.001). There were no main effects or interactions as a function of group for any analyses (Fs < 0.79, Ps > 0.38), suggesting no decrements or enhancements in conflict-related control and adjustment processes or response inhibition for those walking on a treadmill versus sitting. We conclude that cognitive control performance remains relatively unaffected during slow treadmill walking relative to sitting. PMID:26074861
Larson, Michael J.; LeCheminant, James D.; Carbine, Kaylie; Hill, Kyle R.; Christenson, Edward; Masterson, Travis; LeCheminant, Rick
2015-01-01
An increasing trend in the workplace is for employees to walk on treadmills while working to attain known health benefits; however, the effect of walking on a treadmill during cognitive control and executive function tasks is not well known. We compared the cognitive control processes of conflict adaptation (i.e., congruency sequence effects—improved performance following high-conflict relative to low-conflict trials), post-error slowing (i.e., Rabbitt effect), and response inhibition during treadmill walking (1.5 mph) relative to sitting. Understanding the influence of treadmill desks on these cognitive processes may have implications for worker health and productivity. Sixty-nine individuals were randomized to either a sitting (n = 35) or treadmill-walking condition (n = 34). Groups did not differ in age or body mass index. All participants completed a computerized Eriksen flanker task and a response-inhibition go/no-go task in random order while either walking on a treadmill or seated. Response times (RTs) and accuracy were analyzed separately for each task using mixed model analysis of variance. Separate ANOVAs for RTs and accuracy showed the expected conflict adaptation effects, post-error slowing, and response inhibition effects when collapsed across sitting and treadmill groups (all Fs > 78.77, Ps < 0.001). There were no main effects or interactions as a function of group for any analyses (Fs < 0.79, Ps > 0.38), suggesting no decrements or enhancements in conflict-related control and adjustment processes or response inhibition for those walking on a treadmill versus sitting. We conclude that cognitive control performance remains relatively unaffected during slow treadmill walking relative to sitting. PMID:26074861
Retransmission error control with memory
NASA Technical Reports Server (NTRS)
Sindhu, P. S.
1977-01-01
In this paper, an error control technique that is a basic improvement over automatic-repeat-request ARQ is presented. Erroneously received blocks in an ARQ system are used for error control. The technique is termed ARQ-with-memory (MRQ). The general MRQ system is described, and simple upper and lower bounds are derived on the throughput achievable by MRQ. The performance of MRQ with respect to throughput, message delay and probability of error is compared to that of ARQ by simulating both systems using error data from a VHF satellite channel being operated in the ALOHA packet broadcasting mode.
Adaptive nonlinear flight control
NASA Astrophysics Data System (ADS)
Rysdyk, Rolf Theoduor
1998-08-01
Research under supervision of Dr. Calise and Dr. Prasad at the Georgia Institute of Technology, School of Aerospace Engineering. has demonstrated the applicability of an adaptive controller architecture. The architecture successfully combines model inversion control with adaptive neural network (NN) compensation to cancel the inversion error. The tiltrotor aircraft provides a specifically interesting control design challenge. The tiltrotor aircraft is capable of converting from stable responsive fixed wing flight to unstable sluggish hover in helicopter configuration. It is desirable to provide the pilot with consistency in handling qualities through a conversion from fixed wing flight to hover. The linear model inversion architecture was adapted by providing frequency separation in the command filter and the error-dynamics, while not exiting the actuator modes. This design of the architecture provides for a model following setup with guaranteed performance. This in turn allowed for convenient implementation of guaranteed handling qualities. A rigorous proof of boundedness is presented making use of compact sets and the LaSalle-Yoshizawa theorem. The analysis allows for the addition of the e-modification which guarantees boundedness of the NN weights in the absence of persistent excitation. The controller is demonstrated on the Generic Tiltrotor Simulator of Bell-Textron and NASA Ames R.C. The model inversion implementation is robustified with respect to unmodeled input dynamics, by adding dynamic nonlinear damping. A proof of boundedness of signals in the system is included. The effectiveness of the robustification is also demonstrated on the XV-15 tiltrotor. The SHL Perceptron NN provides a more powerful application, based on the universal approximation property of this type of NN. The SHL NN based architecture is also robustified with the dynamic nonlinear damping. A proof of boundedness extends the SHL NN augmentation with robustness to unmodeled actuator
Robust Optimal Adaptive Control Method with Large Adaptive Gain
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2009-01-01
In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.
Criticality of Adaptive Control Dynamics
NASA Astrophysics Data System (ADS)
Patzelt, Felix; Pawelzik, Klaus
2011-12-01
We show, that stabilization of a dynamical system can annihilate observable information about its structure. This mechanism induces critical points as attractors in locally adaptive control. It also reveals, that previously reported criticality in simple controllers is caused by adaptation and not by other controller details. We apply these results to a real-system example: human balancing behavior. A model of predictive adaptive closed-loop control subject to some realistic constraints is introduced and shown to reproduce experimental observations in unprecedented detail. Our results suggests, that observed error distributions in between the Lévy and Gaussian regimes may reflect a nearly optimal compromise between the elimination of random local trends and rare large errors.
Effects of incomplete adaptation and disturbance in adaptive control.
NASA Technical Reports Server (NTRS)
Lindorff, D. P.
1972-01-01
In this paper consideration is given to the effects of disturbance and incomplete parameter adaptation on the performance of adaptive control systems in which Liapunov theory is used in deriving the control law. A design equation for the bounded error is derived. It is further shown that parameters in the adaptive controller may not converge in the presence of disturbance unless the input signal has a rich enough frequency constant. Design examples are presented.
Feedback Error Learning in neuromotor control
NASA Astrophysics Data System (ADS)
Ishihara, Abraham K.
This thesis is concerned with adaptive human motor control. Adaptation is a highly desirable characteristic of any biological system. Failure is an undesirable, yet very real, characteristic of the human motor control systems. Variability is a ubiquitous observation in human movements that has no direct analogue in the design and analysis of robotic control algorithms. This thesis attempts to link these three aspects of motor control under the constraints of a biologically inspired control framework termed Feedback Error Learning (FEL). Utilizing nonlinear and adaptive control methods we prove conditions for which the FEL framework is stable and successful learning can occur. Utilizing singular perturbation methods, we derive conditions for which the system is guaranteed to fail. Variability is analyzed using Ito Calculus and stochastic Lyapunov functionals where signal dependent noise, a commonly observed phenomenon, enters in the learning algorithm. We also show how signal dependent noise might benefit biological control systems despite the inherent variability introduced into the motor control loops. Lastly, we investigate a force tracking control task, where subjects are asked to track a time-varying plant. Using basic control and system identification techniques, we probe the human motor learning system and extract learning rates with respect to the FEL model.
Shelhamer, Mark
2014-01-01
Adaptive processes are crucial in maintaining the accuracy of body movements and rely on error storage and processing mechanisms. Although classically studied with adaptation paradigms, evidence of these ongoing error-correction mechanisms should also be detectable in other movements. Despite this connection, current adaptation models are challenged when forecasting adaptation ability with measures of baseline behavior. On the other hand, we have previously identified an error-correction process present in a particular form of baseline behavior, the generation of predictive saccades. This process exhibits long-term intertrial correlations that decay gradually (as a power law) and are best characterized with the tools of fractal time series analysis. Since this baseline task and adaptation both involve error storage and processing, we sought to find a link between the intertrial correlations of the error-correction process in predictive saccades and the ability of subjects to alter their saccade amplitudes during an adaptation task. Here we find just such a relationship: the stronger the intertrial correlations during prediction, the more rapid the acquisition of adaptation. This reinforces the links found previously between prediction and adaptation in motor control and suggests that current adaptation models are inadequate to capture the complete dynamics of these error-correction processes. A better understanding of the similarities in error processing between prediction and adaptation might provide the means to forecast adaptation ability with a baseline task. This would have many potential uses in physical therapy and the general design of paradigms of motor adaptation. PMID:24598520
Plessen, Kerstin J.; Allen, Elena A.; Eichele, Heike; van Wageningen, Heidi; Høvik, Marie Farstad; Sørensen, Lin; Worren, Marius Kalsås; Hugdahl, Kenneth; Eichele, Tom
2016-01-01
Background We examined the blood-oxygen level–dependent (BOLD) activation in brain regions that signal errors and their association with intraindividual behavioural variability and adaptation to errors in children with attention-deficit/hyperactivity disorder (ADHD). Methods We acquired functional MRI data during a Flanker task in medication-naive children with ADHD and healthy controls aged 8–12 years and analyzed the data using independent component analysis. For components corresponding to performance monitoring networks, we compared activations across groups and conditions and correlated them with reaction times (RT). Additionally, we analyzed post-error adaptations in behaviour and motor component activations. Results We included 25 children with ADHD and 29 controls in our analysis. Children with ADHD displayed reduced activation to errors in cingulo-opercular regions and higher RT variability, but no differences of interference control. Larger BOLD amplitude to error trials significantly predicted reduced RT variability across all participants. Neither group showed evidence of post-error response slowing; however, post-error adaptation in motor networks was significantly reduced in children with ADHD. This adaptation was inversely related to activation of the right-lateralized ventral attention network (VAN) on error trials and to task-driven connectivity between the cingulo-opercular system and the VAN. Limitations Our study was limited by the modest sample size and imperfect matching across groups. Conclusion Our findings show a deficit in cingulo-opercular activation in children with ADHD that could relate to reduced signalling for errors. Moreover, the reduced orienting of the VAN signal may mediate deficient post-error motor adaptions. Pinpointing general performance monitoring problems to specific brain regions and operations in error processing may help to guide the targets of future treatments for ADHD. PMID:26441332
Adaptive Controller Effects on Pilot Behavior
NASA Technical Reports Server (NTRS)
Trujillo, Anna C.; Gregory, Irene M.; Hempley, Lucas E.
2014-01-01
Adaptive control provides robustness and resilience for highly uncertain, and potentially unpredictable, flight dynamics characteristic. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the software adaptive control system and the pilot. An experiment was conducted to categorize these interactions on the pilot with an adaptive controller during control surface failures. One of the objectives of this experiment was to determine how the adaptation time of the controller affects pilots. The pitch and roll errors, and stick input increased for increasing adaptation time and during the segment when the adaptive controller was adapting. Not surprisingly, altitude, cross track and angle deviations, and vertical velocity also increase during the failure and then slowly return to pre-failure levels. Subjects may change their behavior even as an adaptive controller is adapting with additional stick inputs. Therefore, the adaptive controller should adapt as fast as possible to minimize flight track errors. This will minimize undesirable interactions between the pilot and the adaptive controller and maintain maneuvering precision.
Decentralized adaptive control
NASA Technical Reports Server (NTRS)
Oh, B. J.; Jamshidi, M.; Seraji, H.
1988-01-01
A decentralized adaptive control is proposed to stabilize and track the nonlinear, interconnected subsystems with unknown parameters. The adaptation of the controller gain is derived by using model reference adaptive control theory based on Lyapunov's direct method. The adaptive gains consist of sigma, proportional, and integral combination of the measured and reference values of the corresponding subsystem. The proposed control is applied to the joint control of a two-link robot manipulator, and the performance in computer simulation corresponds with what is expected in theoretical development.
Finite element error estimation and adaptivity based on projected stresses
Jung, J.
1990-08-01
This report investigates the behavior of a family of finite element error estimators based on projected stresses, i.e., continuous stresses that are a least squared error fit to the conventional Gauss point stresses. An error estimate based on element force equilibrium appears to be quite effective. Examples of adaptive mesh refinement for a one-dimensional problem are presented. Plans for two-dimensional adaptivity are discussed. 12 refs., 82 figs.
Adaptive Controller Adaptation Time and Available Control Authority Effects on Piloting
NASA Technical Reports Server (NTRS)
Trujillo, Anna; Gregory, Irene
2013-01-01
Adaptive control is considered for highly uncertain, and potentially unpredictable, flight dynamics characteristic of adverse conditions. This experiment looked at how adaptive controller adaptation time to recover nominal aircraft dynamics affects pilots and how pilots want information about available control authority transmitted. Results indicate that an adaptive controller that takes three seconds to adapt helped pilots when looking at lateral and longitudinal errors. The controllability ratings improved with the adaptive controller, again the most for the three seconds adaptation time while workload decreased with the adaptive controller. The effects of the displays showing the percentage amount of available safe flight envelope used in the maneuver were dominated by the adaptation time. With the displays, the altitude error increased, controllability slightly decreased, and mental demand increased. Therefore, the displays did require some of the subjects resources but these negatives may be outweighed by pilots having more situation awareness of their aircraft.
Adaptation of bit error rate by coding
NASA Astrophysics Data System (ADS)
Marguinaud, A.; Sorton, G.
1984-07-01
The use of coding in spacecraft wideband communication to reduce power transmission, save bandwith, and lower antenna specifications was studied. The feasibility of a coder decoder functioning at a bit rate of 10 Mb/sec with a raw bit error rate (BER) of 0.001 and an output BER of 0.000000001 is demonstrated. A single block code protection, and two coding levels protection are examined. A single level protection BCH code with 5 errors correction capacity, 16% redundancy, and interleaving depth 4 giving a coded block of 1020 bits is simple to implement, but has BER = 0.000000007. A single level BCH code with 7 errors correction capacity and 12% redundancy meets specifications, but is more difficult to implement. Two level protection with 9% BCH outer and 10% BCH inner codes, both levels with 3 errors correction capacity and 8% redundancy for a coded block of 7050 bits is the most complex, but offers performance advantages.
Automatic-repeat-request error control schemes
NASA Technical Reports Server (NTRS)
Lin, S.; Costello, D. J., Jr.; Miller, M. J.
1983-01-01
Error detection incorporated with automatic-repeat-request (ARQ) is widely used for error control in data communication systems. This method of error control is simple and provides high system reliability. If a properly chosen code is used for error detection, virtually error-free data transmission can be attained. Various types of ARQ and hybrid ARQ schemes, and error detection using linear block codes are surveyed.
Error Signals in Motor Cortices Drive Adaptation in Reaching.
Inoue, Masato; Uchimura, Motoaki; Kitazawa, Shigeru
2016-06-01
Reaching movements are subject to adaptation in response to errors induced by prisms or external perturbations. Motor cortical circuits have been hypothesized to provide execution errors that drive adaptation, but human imaging studies to date have reported that execution errors are encoded in parietal association areas. Thus, little evidence has been uncovered that supports the motor hypothesis. Here, we show that both primary motor and premotor cortices encode information on end-point errors in reaching. We further show that post-movement microstimulation to these regions caused trial-by-trial increases in errors, which subsided exponentially when the stimulation was terminated. The results indicate for the first time that motor cortical circuits provide error signals that drive trial-by-trial adaptation in reaching movements. PMID:27181058
Adaptive error correction codes for face identification
NASA Astrophysics Data System (ADS)
Hussein, Wafaa R.; Sellahewa, Harin; Jassim, Sabah A.
2012-06-01
Face recognition in uncontrolled environments is greatly affected by fuzziness of face feature vectors as a result of extreme variation in recording conditions (e.g. illumination, poses or expressions) in different sessions. Many techniques have been developed to deal with these variations, resulting in improved performances. This paper aims to model template fuzziness as errors and investigate the use of error detection/correction techniques for face recognition in uncontrolled environments. Error correction codes (ECC) have recently been used for biometric key generation but not on biometric templates. We have investigated error patterns in binary face feature vectors extracted from different image windows of differing sizes and for different recording conditions. By estimating statistical parameters for the intra-class and inter-class distributions of Hamming distances in each window, we encode with appropriate ECC's. The proposed approached is tested for binarised wavelet templates using two face databases: Extended Yale-B and Yale. We shall demonstrate that using different combinations of BCH-based ECC's for different blocks and different recording conditions leads to in different accuracy rates, and that using ECC's results in significantly improved recognition results.
Error magnitude estimation in model-reference adaptive systems
NASA Technical Reports Server (NTRS)
Colburn, B. K.; Boland, J. S., III
1975-01-01
A second order approximation is derived from a linearized error characteristic equation for Lyapunov designed model-reference adaptive systems and is used to estimate the maximum error between the model and plant states, and the time to reach this peak following a plant perturbation. The results are applicable in the analysis of plants containing magnitude-dependent nonlinearities.
Visuomotor adaptation needs a validation of prediction error by feedback error
Gaveau, Valérie; Prablanc, Claude; Laurent, Damien; Rossetti, Yves; Priot, Anne-Emmanuelle
2014-01-01
The processes underlying short-term plasticity induced by visuomotor adaptation to a shifted visual field are still debated. Two main sources of error can induce motor adaptation: reaching feedback errors, which correspond to visually perceived discrepancies between hand and target positions, and errors between predicted and actual visual reafferences of the moving hand. These two sources of error are closely intertwined and difficult to disentangle, as both the target and the reaching limb are simultaneously visible. Accordingly, the goal of the present study was to clarify the relative contributions of these two types of errors during a pointing task under prism-displaced vision. In “terminal feedback error” condition, viewing of their hand by subjects was allowed only at movement end, simultaneously with viewing of the target. In “movement prediction error” condition, viewing of the hand was limited to movement duration, in the absence of any visual target, and error signals arose solely from comparisons between predicted and actual reafferences of the hand. In order to prevent intentional corrections of errors, a subthreshold, progressive stepwise increase in prism deviation was used, so that subjects remained unaware of the visual deviation applied in both conditions. An adaptive aftereffect was observed in the “terminal feedback error” condition only. As far as subjects remained unaware of the optical deviation and self-assigned pointing errors, prediction error alone was insufficient to induce adaptation. These results indicate a critical role of hand-to-target feedback error signals in visuomotor adaptation; consistent with recent neurophysiological findings, they suggest that a combination of feedback and prediction error signals is necessary for eliciting aftereffects. They also suggest that feedback error updates the prediction of reafferences when a visual perturbation is introduced gradually and cognitive factors are eliminated or strongly
A neural fuzzy controller learning by fuzzy error propagation
NASA Technical Reports Server (NTRS)
Nauck, Detlef; Kruse, Rudolf
1992-01-01
In this paper, we describe a procedure to integrate techniques for the adaptation of membership functions in a linguistic variable based fuzzy control environment by using neural network learning principles. This is an extension to our work. We solve this problem by defining a fuzzy error that is propagated back through the architecture of our fuzzy controller. According to this fuzzy error and the strength of its antecedent each fuzzy rule determines its amount of error. Depending on the current state of the controlled system and the control action derived from the conclusion, each rule tunes the membership functions of its antecedent and its conclusion. By this we get an unsupervised learning technique that enables a fuzzy controller to adapt to a control task by knowing just about the global state and the fuzzy error.
NASA Technical Reports Server (NTRS)
Narendra, K. S.; Annaswamy, A. M.
1985-01-01
Several concepts and results in robust adaptive control are are discussed and is organized in three parts. The first part surveys existing algorithms. Different formulations of the problem and theoretical solutions that have been suggested are reviewed here. The second part contains new results related to the role of persistent excitation in robust adaptive systems and the use of hybrid control to improve robustness. In the third part promising new areas for future research are suggested which combine different approaches currently known.
A posteriori error estimator and error control for contact problems
NASA Astrophysics Data System (ADS)
Weiss, Alexander; Wohlmuth, Barbara I.
2009-09-01
In this paper, we consider two error estimators for one-body contact problems. The first error estimator is defined in terms of H( div ) -conforming stress approximations and equilibrated fluxes while the second is a standard edge-based residual error estimator without any modification with respect to the contact. We show reliability and efficiency for both estimators. Moreover, the error is bounded by the first estimator with a constant one plus a higher order data oscillation term plus a term arising from the contact that is shown numerically to be of higher order. The second estimator is used in a control-based AFEM refinement strategy, and the decay of the error in the energy is shown. Several numerical tests demonstrate the performance of both estimators.
Adaptive periodic error correction for the VLT telescopes
NASA Astrophysics Data System (ADS)
Erm, Toomas; Sandrock, Stefan
2003-02-01
As a further step to improve the excellent tracking performance of the VLT telescopes, the intrinsic errors in the telescope drive systems are analysed. These errors fall into two categories, torque disturbances and sensor errors and they have different impact on the performance. Models for the errors are developed and algorithms for on line adaptive parameter identification are presented. The models can be used to significantly reduce the influence of the errors and also to monitor parameters like friction and unbalance. The VLT servo model is used to test and verify the models and algorithms. It follows a description of the real-time software aspects of the algorithms, which have been implemented for VxWorks-based systems. The software design allows various options for the adaptation of the process coefficients, either running permanently in background, only on demand through maintenance procedures, or fixed off-line modeling based on recorded process data. Finally, real test data are presented.
Error Argumentation Enhance Adaptability in Adults With Low Motor Ability.
Lee, Chi-Mei; Bo, Jin
2016-01-01
The authors focused on young adults with varying degrees of motor difficulties and examined their adaptability in a visuomotor adaptation task where the visual feedback of participants' movement error was presented with either 1:1 ratio (i.e., regular feedback schedule) or 1:2 ratio (i.e., enhanced feedback schedule). Within-subject design was used with two feedback schedules counter-balanced and separated for 10 days. Results revealed that participants with greater motor difficulties showed less adaptability than those with normal motor abilities in the regular feedback schedule; however, all participants demonstrated similar level of adaptability in the enhanced feedback schedule. The results suggest that error argumentation enhances adaptability in adults with low motor ability. PMID:26672393
A cascaded coding scheme for error control
NASA Technical Reports Server (NTRS)
Kasami, T.; Lin, S.
1985-01-01
A cascaded coding scheme for error control was investigated. The scheme employs a combination of hard and soft decisions in decoding. Error performance is analyzed. If the inner and outer codes are chosen properly, extremely high reliability can be attained even for a high channel bit-error-rate. Some example schemes are studied which seem to be quite suitable for satellite down-link error control.
A concatenated coding scheme for error control
NASA Technical Reports Server (NTRS)
Lin, S.
1985-01-01
A concatenated coding scheme for error contol in data communications was analyzed. The inner code is used for both error correction and detection, however the outer code is used only for error detection. A retransmission is requested if either the inner code decoder fails to make a successful decoding or the outer code decoder detects the presence of errors after the inner code decoding. Probability of undetected error of the proposed scheme is derived. An efficient method for computing this probability is presented. Throughout efficiency of the proposed error control scheme incorporated with a selective repeat ARQ retransmission strategy is analyzed.
Repair of streaming multimedia with adaptive forward error correction
NASA Astrophysics Data System (ADS)
French, Kenneth; Claypool, Mark
2001-11-01
Internet multimedia applications have timing constraints that are often not met by TCP, the de facto Internet transport protocol, hence, most multimedia applications use UDP. Since UDP does not guarantee data arrival, UDP flows often have high data loss rates. Network data loss can be ameliorated by the use of Forward Error Compression (FEC), where a server adds redundant data to the flow to help the client repair lost data. However, the effectiveness of FEC depends upon the network burst loss rates, and current FEC approaches are non-adaptive or adapt without effectively monitoring this rate. We propose a Forward Error Correction protocol that explicitly adapts the redundancy to the measured network burst loss rates. Through evaluation under a variety of network conditions, we find our adaptive FEC approach achieves minimal end-to-end delay and low loss rates after repair.
Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2012-01-01
This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.
Adaptive signed distance transform for curves with guaranteed error bounds
Laney, D A; Duchaineau, M A; Max, N L
2000-12-04
We present an adaptive signed distance transform algorithm for curves in the plane. The algorithm provides guaranteed error bounds with a selective refinement approach. The domain over which the signed distance function is desired is adaptive triangulated and piecewise discontinuous linear approximations are constructed within each triangle. The resulting transform performs work only were requested and does not rely on a preset sampling rate or other constraints.
An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan
2008-01-01
This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.
Adaptive sequential controller
El-Sharkawi, Mohamed A.; Xing, Jian; Butler, Nicholas G.; Rodriguez, Alonso
1994-01-01
An adaptive sequential controller (50/50') for controlling a circuit breaker (52) or other switching device to substantially eliminate transients on a distribution line caused by closing and opening the circuit breaker. The device adaptively compensates for changes in the response time of the circuit breaker due to aging and environmental effects. A potential transformer (70) provides a reference signal corresponding to the zero crossing of the voltage waveform, and a phase shift comparator circuit (96) compares the reference signal to the time at which any transient was produced when the circuit breaker closed, producing a signal indicative of the adaptive adjustment that should be made. Similarly, in controlling the opening of the circuit breaker, a current transformer (88) provides a reference signal that is compared against the time at which any transient is detected when the circuit breaker last opened. An adaptive adjustment circuit (102) produces a compensation time that is appropriately modified to account for changes in the circuit breaker response, including the effect of ambient conditions and aging. When next opened or closed, the circuit breaker is activated at an appropriately compensated time, so that it closes when the voltage crosses zero and opens when the current crosses zero, minimizing any transients on the distribution line. Phase angle can be used to control the opening of the circuit breaker relative to the reference signal provided by the potential transformer.
Diederen, Kelly M J; Spencer, Tom; Vestergaard, Martin D; Fletcher, Paul C; Schultz, Wolfram
2016-06-01
Effective error-driven learning benefits from scaling of prediction errors to reward variability. Such behavioral adaptation may be facilitated by neurons coding prediction errors relative to the standard deviation (SD) of reward distributions. To investigate this hypothesis, we required participants to predict the magnitude of upcoming reward drawn from distributions with different SDs. After each prediction, participants received a reward, yielding trial-by-trial prediction errors. In line with the notion of adaptive coding, BOLD response slopes in the Substantia Nigra/Ventral Tegmental Area (SN/VTA) and ventral striatum were steeper for prediction errors occurring in distributions with smaller SDs. SN/VTA adaptation was not instantaneous but developed across trials. Adaptive prediction error coding was paralleled by behavioral adaptation, as reflected by SD-dependent changes in learning rate. Crucially, increased SN/VTA and ventral striatal adaptation was related to improved task performance. These results suggest that adaptive coding facilitates behavioral adaptation and supports efficient learning. PMID:27181060
NASA Astrophysics Data System (ADS)
Reif, Konrad
Die adaptive Fahrgeschwindigkeitsregelung (ACC, Adaptive Cruise Control) ist eine Weiterentwicklung der konventionellen Fahrgeschwindigkeitsregelung, die eine konstante Fahrgeschwindigkeit einstellt. ACC überwacht mittels eines Radarsensors den Bereich vor dem Fahrzeug und passt die Geschwindigkeit den Gegebenheiten an. ACC reagiert auf langsamer vorausfahrende oder einscherende Fahrzeuge mit einer Reduzierung der Geschwindigkeit, sodass der vorgeschriebene Mindestabstand zum vorausfahrenden Fahrzeug nicht unterschritten wird. Hierzu greift ACC in Antrieb und Bremse ein. Sobald das vorausfahrende Fahrzeug beschleunigt oder die Spur verlässt, regelt ACC die Geschwindigkeit wieder auf die vorgegebene Sollgeschwindigkeit ein (Bild 1). ACC steht somit für eine Geschwindigkeitsregelung, die sich dem vorausfahrenden Verkehr anpasst.
Structured near-optimal channel-adapted quantum error correction
NASA Astrophysics Data System (ADS)
Fletcher, Andrew S.; Shor, Peter W.; Win, Moe Z.
2008-01-01
We present a class of numerical algorithms which adapt a quantum error correction scheme to a channel model. Given an encoding and a channel model, it was previously shown that the quantum operation that maximizes the average entanglement fidelity may be calculated by a semidefinite program (SDP), which is a convex optimization. While optimal, this recovery operation is computationally difficult for long codes. Furthermore, the optimal recovery operation has no structure beyond the completely positive trace-preserving constraint. We derive methods to generate structured channel-adapted error recovery operations. Specifically, each recovery operation begins with a projective error syndrome measurement. The algorithms to compute the structured recovery operations are more scalable than the SDP and yield recovery operations with an intuitive physical form. Using Lagrange duality, we derive performance bounds to certify near-optimality.
A Nonlinear Adaptive Filter for Gyro Thermal Bias Error Cancellation
NASA Technical Reports Server (NTRS)
Galante, Joseph M.; Sanner, Robert M.
2012-01-01
Deterministic errors in angular rate gyros, such as thermal biases, can have a significant impact on spacecraft attitude knowledge. In particular, thermal biases are often the dominant error source in MEMS gyros after calibration. Filters, such as J\\,fEKFs, are commonly used to mitigate the impact of gyro errors and gyro noise on spacecraft closed loop pointing accuracy, but often have difficulty in rapidly changing thermal environments and can be computationally expensive. In this report an existing nonlinear adaptive filter is used as the basis for a new nonlinear adaptive filter designed to estimate and cancel thermal bias effects. A description of the filter is presented along with an implementation suitable for discrete-time applications. A simulation analysis demonstrates the performance of the filter in the presence of noisy measurements and provides a comparison with existing techniques.
Effects of incomplete adaption and disturbance in adaptive control
NASA Technical Reports Server (NTRS)
Lindorff, D. P.
1972-01-01
This investigation focused attention on the fact that the synthesis of adaptive control systems has often been discussed in the framework of idealizations which may represent over simplifications. A condition for boundedness of the tracking error has been derived for the case in which incomplete adaption and disturbance are present. When using Parks' design it is shown that instability of the adaptive gains can result due to the presence of disturbance. The theory has been applied to a nontrivial example in order to illustrate the concepts involved.
Adaptive periodic error correction for Heidenhain tape encoders
NASA Astrophysics Data System (ADS)
Warner, Michael; Krabbendam, Victor; Schumacher, German
2008-07-01
Heidenhain position tape encoders are in use on almost all modern telescopes with excellent results. Performance of these systems can be limited by minor mechanical misalignments between the tape and read head causing errors at the grating period. The first and second harmonics of the measured signal are the dominant errors, and have a varying frequency dependant on axis rate. When the error spectrum is within the mount servo bandwidth it results in periodic telescope pointing jitter. This paper will describe an adaptive error correction using elliptic interpolation of the raw signals, based on the well known compensation technique developed by Heydemann [1]. The approach allows the compensation to track in real time with no need of a large static look-up table, or frequent calibrations. This paper also presents the results obtained after applying this approach on data measured on the SOAR telescope.
Adaptation to sensory-motor reflex perturbations is blind to the source of errors
Hudson, Todd E.; Landy, Michael S.
2012-01-01
In the study of visual-motor control, perhaps the most familiar findings involve adaptation to externally imposed movement errors. Theories of visual-motor adaptation based on optimal information processing suppose that the nervous system identifies the sources of errors to effect the most efficient adaptive response. We report two experiments using a novel perturbation based on stimulating a visually induced reflex in the reaching arm. Unlike adaptation to an external force, our method induces a perturbing reflex within the motor system itself, i.e., perturbing forces are self-generated. This novel method allows a test of the theory that error-source information is used to generate an optimal adaptive response. If the self-generated source of the visually-induced reflex perturbation is identified, the optimal response will be via reflex gain control. If the source is not identified, a compensatory force should be generated to counteract the reflex. Gain control is the optimal response to reflex perturbation, both because energy cost and movement errors are minimized. Energy is conserved because neither reflex-induced nor compensatory forces are generated. Precision is maximized because endpoint variance is proportional to force production. We find evidence against source-identified adaptation in both experiments, suggesting that sensory-motor information processing is not always optimal. PMID:22228797
Adaptive Femtosecond Quantum Control
NASA Astrophysics Data System (ADS)
Gerber, Gustav
2003-03-01
Obtaining active control over the dynamics of quantum-mechanical systems is a fascinating perspective in modern physics. A promising tool for this purpose is available with femtosecond laser technologies. The intrinsically broad spectral distribution and the phase function of femtosecond laser pulses can be specifically manipulated by pulse shapers to drive molecular systems coherently into the desired reaction pathways [1]. The approach of adaptive femtosecond quantum control follows the suggestion of Judson and Rabitz [2], in which a computer-controlled pulse shaper is used in combination with a learning algorithm [3] and direct feedback from the experiment to achieve coherent control over quantum-mechanical processes in an automated fashion, without requiring any model for the system's response. This technique can be applied to the control of gas-phase photodissociation processes [4]. Different bond-cleaving reactions can be preferentially selected, resulting in chemically different products. Prior knowledge about molecular Hamiltonians or reaction mechanisms is not required in this automated control loop, and this scheme works for complex systems. Adaptive pulse-shaping techniques can be transferred to the control of photoprocesses in the liquid phase as well, motivated by the wish to achieve control at particle densities high enough for (bimolecular) synthetic-chemical applications. Chemically selective molecular excitation is achieved by many-parameter adaptive quantum control [5], despite the failure of typical single-parameter approaches (such as wavelength control, intensity control, or linear chirp control). This experiment demonstrates that photoprocesses in two different molecular species can be controlled simultaneously. Applications are envisioned in bimolecular reaction control where specific educt molecules could selectively be "activated" for purposes of chemical synthesis. A new technological development further increases the possibilities and
Adaptive feedback active noise control
NASA Astrophysics Data System (ADS)
Kuo, Sen M.; Vijayan, Dipa
Feedforward active noise control (ANC) systems use a reference sensor that senses a reference input to the controller. This signal is assumed to be unaffected by the secondary source and is a good measure of the undesired noise to be cancelled by the system. The reference sensor may be acoustic (e.g., microphone) or non-acoustic (e.g., tachometer, optical transducer). An obvious problem when using acoustic sensors is that the reference signal may be corrupted by the canceling signal generated by the secondary source. This problem is known as acoustic feedback. One way of avoiding this is by using a feedback active noise control (FANC) system which dispenses with the reference sensor. The FANC technique originally proposed by Olson and May employs a high gain negative feedback amplifier. This system suffered from the drawback that the error microphone had to be placed very close to the loudspeaker. The operation of the system was restricted to low frequency range and suffered from instability due to the possibility of positive feedback. Feedback systems employing adaptive filtering techniques for active noise control were developed. This paper presents the FANC system modeled as an adaptive prediction scheme.
Adaptive control: Myths and realities
NASA Technical Reports Server (NTRS)
Athans, M.; Valavani, L.
1984-01-01
It was found that all currently existing globally stable adaptive algorithms have three basic properties in common: positive realness of the error equation, square-integrability of the parameter adjustment law and, need for sufficient excitation for asymptotic parameter convergence. Of the three, the first property is of primary importance since it satisfies a sufficient condition for stabillity of the overall system, which is a baseline design objective. The second property has been instrumental in the proof of asymptotic error convergence to zero, while the third addresses the issue of parameter convergence. Positive-real error dynamics can be generated only if the relative degree (excess of poles over zeroes) of the process to be controlled is known exactly; this, in turn, implies perfect modeling. This and other assumptions, such as absence of nonminimum phase plant zeros on which the mathematical arguments are based, do not necessarily reflect properties of real systems. As a result, it is natural to inquire what happens to the designs under less than ideal assumptions. The issues arising from violation of the exact modeling assumption which is extremely restrictive in practice and impacts the most important system property, stability, are discussed.
Linearization of Attitude-Control Error Dynamics
NASA Technical Reports Server (NTRS)
Bach, Ralph; Paielli, Russell
1993-01-01
Direction cosines and quaternions are useful for representing rigid-body attitude because they exhibit no kinematic singularities. Each utilizes more variables than the minimum three degrees of freedom required to specify attitude. Therefore, application of a nonlinear inversion procedure to either formulation introduces singularities. Furthermore, in designing an attitude-control system, it is not appropriate to express attitude error as a difference of direction cosines (or quaternions). One should employ a measure of attitude error that not only is minimal but preserves orthogonal rotation properties as well. This note applies an inversion procedure to an appropriate measure of attitude error, so that the singularity occurs when the error reaches +/- 180 deg. This approach leads to the realization of a new model-follower attitude-control system that exhibits exact linear attitude-error dynamics.
The successively temporal error concealment algorithm using error-adaptive block matching principle
NASA Astrophysics Data System (ADS)
Lee, Yu-Hsuan; Wu, Tsai-Hsing; Chen, Chao-Chyun
2014-09-01
Generally, the temporal error concealment (TEC) adopts the blocks around the corrupted block (CB) as the search pattern to find the best-match block in previous frame. Once the CB is recovered, it is referred to as the recovered block (RB). Although RB can be the search pattern to find the best-match block of another CB, RB is not the same as its original block (OB). The error between the RB and its OB limits the performance of TEC. The successively temporal error concealment (STEC) algorithm is proposed to alleviate this error. The STEC procedure consists of tier-1 and tier-2. The tier-1 divides a corrupted macroblock into four corrupted 8 × 8 blocks and generates a recovering order for them. The corrupted 8 × 8 block with the first place of recovering order is recovered in tier-1, and remaining 8 × 8 CBs are recovered in tier-2 along the recovering order. In tier-2, the error-adaptive block matching principle (EA-BMP) is proposed for the RB as the search pattern to recover remaining corrupted 8 × 8 blocks. The proposed STEC outperforms sophisticated TEC algorithms on average PSNR by 0.3 dB on the packet error rate of 20% at least.
Xu, Jing; Klemfuss, Nola M.; Griffiths, Thomas L.; Ivry, Richard B.
2013-01-01
The cerebellum has long been recognized to play an important role in motor adaptation. Individuals with cerebellar ataxia exhibit impaired learning in visuomotor adaptation tasks such as prism adaptation and force field learning. Both types of tasks involve the adjustment of an internal model to compensate for an external perturbation. This updating process is error driven, with the error signal based on the difference between anticipated and actual sensory information. This process may entail a credit assignment problem, with a distinction made between error arising from faulty representation of the environment and error arising from noise in the controller. We hypothesized that people with ataxia may perform poorly at visuomotor adaptation because they attribute a greater proportion of their error to their motor control difficulties. We tested this hypothesis using a computational model based on a Kalman filter. We imposed a 20-deg visuomotor rotation in either a single large step or in a series of smaller 5-deg steps. The ataxic group exhibited a comparable deficit in both conditions. The computational analyses indicate that the patients' deficit cannot be accounted for simply by their increased motor variability. Rather, the patients' deficit in learning may be related to difficulty in estimating the instability in the environment or variability in their motor system. PMID:23197450
A concatenated coding scheme for error control
NASA Technical Reports Server (NTRS)
Lin, S.
1985-01-01
A concatenated coding scheme for error control in data communications is analyzed. The inner code is used for both error correction and detection, however the outer code is used only for error detection. A retransmission is requested if the outer code detects the presence of errors after the inner code decoding. The probability of undetected error of the above error control scheme is derived and upper bounded. Two specific exmaples are analyzed. In the first example, the inner code is a distance-4 shortened Hamming code with generator polynomial (X+1)(X(6)+X+1) = X(7)+X(6)+X(2)+1 and the outer code is a distance-4 shortened Hamming code with generator polynomial (X+1)X(15+X(14)+X(13)+X(12)+X(4)+X(3)+X(2)+X+1) = X(16)+X(12)+X(5)+1 which is the X.25 standard for packet-switched data network. This example is proposed for error control on NASA telecommand links. In the second example, the inner code is the same as that in the first example but the outer code is a shortened Reed-Solomon code with symbols from GF(2(8)) and generator polynomial (X+1)(X+alpha) where alpha is a primitive element in GF(z(8)).
Adaptive Error Estimation in Linearized Ocean General Circulation Models
NASA Technical Reports Server (NTRS)
Chechelnitsky, Michael Y.
1999-01-01
Data assimilation methods are routinely used in oceanography. The statistics of the model and measurement errors need to be specified a priori. This study addresses the problem of estimating model and measurement error statistics from observations. We start by testing innovation based methods of adaptive error estimation with low-dimensional models in the North Pacific (5-60 deg N, 132-252 deg E) to TOPEX/POSEIDON (TIP) sea level anomaly data, acoustic tomography data from the ATOC project, and the MIT General Circulation Model (GCM). A reduced state linear model that describes large scale internal (baroclinic) error dynamics is used. The methods are shown to be sensitive to the initial guess for the error statistics and the type of observations. A new off-line approach is developed, the covariance matching approach (CMA), where covariance matrices of model-data residuals are "matched" to their theoretical expectations using familiar least squares methods. This method uses observations directly instead of the innovations sequence and is shown to be related to the MT method and the method of Fu et al. (1993). Twin experiments using the same linearized MIT GCM suggest that altimetric data are ill-suited to the estimation of internal GCM errors, but that such estimates can in theory be obtained using acoustic data. The CMA is then applied to T/P sea level anomaly data and a linearization of a global GFDL GCM which uses two vertical modes. We show that the CMA method can be used with a global model and a global data set, and that the estimates of the error statistics are robust. We show that the fraction of the GCM-T/P residual variance explained by the model error is larger than that derived in Fukumori et al.(1999) with the method of Fu et al.(1993). Most of the model error is explained by the barotropic mode. However, we find that impact of the change in the error statistics on the data assimilation estimates is very small. This is explained by the large
Engine identification for adaptive control
NASA Technical Reports Server (NTRS)
Leonard, R. G.; Arnett, E. M.
1980-01-01
An attempt to obtain a dynamic model for a turbofan gas turbine engine for the purpose of adaptive control is described. The requirements for adaptive control indicate that a dynamic model should be identified from data sampled during engine operation. The dynamic model identified was of the form of linear differential equations with time varying coefficients. A turbine engine is, however, a highly nonlinear system, so the identified model would be valid only over a small area near the operating point, thus requiring frequent updating of the coefficients in the model. Therefore it is necessary that the identifier use only recent information to perform its function. The identifier selected minimized the square of the equation errors. Known linear systems were used to test the characteristics of the identifier. It was found that the performance was dependent on the number of data points used in the computations and upon the time interval over which the data points were obtained. Preliminary results using an engine deck for the quiet, clean, shorthaul experimental engine indicate that the identified model predicts the engine motion well when there is sufficient dynamic information, that is when the engine is in transient operation.
Efficient hybrid ARQ protocols with adaptive forward error correction
NASA Astrophysics Data System (ADS)
Kallel, Samir
1994-02-01
In this paper, efficient Stop-and-Wait, Go-Back-N , and Selective-Repeat hybrid ARQ protocols with Adaptive Forward Error Correction (AFEC) using convolutional coding are proposed and analyzed. The basic idea is to vary the coding rate for error correction according to system parameters, such as the signal-to-noise ratio, the round trip delay, and the buffer size at the receiver, so as to maximize the throughput efficiency. The performances of the proposed ARQ protocols are evaluated for two channel models: a non-fading and an ideally-interleaved Rayleigh-fading additive white Gaussian noise channel. In all cases, it is found that the hybrid ARQ protocols with AFEC yield a comparatively high throughput under all channel conditions.
Error Correction, Control Systems and Fuzzy Logic
NASA Technical Reports Server (NTRS)
Smith, Earl B.
2004-01-01
This paper will be a discussion on dealing with errors. While error correction and communication is important when dealing with spacecraft vehicles, the issue of control system design is also important. There will be certain commands that one wants a motion device to execute. An adequate control system will be necessary to make sure that the instruments and devices will receive the necessary commands. As it will be discussed later, the actual value will not always be equal to the intended or desired value. Hence, an adequate controller will be necessary so that the gap between the two values will be closed.
Performance of focused error control codes
NASA Astrophysics Data System (ADS)
Alajaji, Fady; Fuja, Thomas
1994-02-01
Consider an additive noise channel with inputs and outputs in the field GF(q) where qgreater than 2; every time a symbol is transmitted over such a channel, there are q - 1 different errors that can occur, corresponding to the q - 1 non-zero elements that the channel can add to the transmitted symbol. In many data communication/storage systems, there are some errors that occur much more frequently than others; however, traditional error correcting codes - designed with respect to the Hamming metric - treat each of these q - 1 errors the same. Fuja and Heegard have designed a class of codes, called focused error control codes, that offer different levels of protection against common and uncommon errors; the idea is to define the level of protection in a way based not only on the number of errors, but the kind as well. In this paper, the performance of these codes is analyzed with respect to idealized 'skewed' channels as well as realistic non-binary modulation schemes. It is shown that focused codes, used in conjunction with PSK and QAM signaling, can provide more than 1.0 dB of additional coding gain when compared with Reed-Solomon codes for small blocklengths.
Error control in the GCF: An information-theoretic model for error analysis and coding
NASA Technical Reports Server (NTRS)
Adeyemi, O.
1974-01-01
The structure of data-transmission errors within the Ground Communications Facility is analyzed in order to provide error control (both forward error correction and feedback retransmission) for improved communication. Emphasis is placed on constructing a theoretical model of errors and obtaining from it all the relevant statistics for error control. No specific coding strategy is analyzed, but references to the significance of certain error pattern distributions, as predicted by the model, to error correction are made.
Hanajima, Ritsuko; Shadmehr, Reza; Ohminami, Shinya; Tsutsumi, Ryosuke; Shirota, Yuichiro; Shimizu, Takahiro; Tanaka, Nobuyuki; Terao, Yasuo; Tsuji, Shoji; Ugawa, Yoshikazu; Uchimura, Motoaki; Inoue, Masato; Kitazawa, Shigeru
2015-10-01
Cerebellar damage can profoundly impair human motor adaptation. For example, if reaching movements are perturbed abruptly, cerebellar damage impairs the ability to learn from the perturbation-induced errors. Interestingly, if the perturbation is imposed gradually over many trials, people with cerebellar damage may exhibit improved adaptation. However, this result is controversial, since the differential effects of gradual vs. abrupt protocols have not been observed in all studies. To examine this question, we recruited patients with pure cerebellar ataxia due to cerebellar cortical atrophy (n = 13) and asked them to reach to a target while viewing the scene through wedge prisms. The prisms were computer controlled, making it possible to impose the full perturbation abruptly in one trial, or build up the perturbation gradually over many trials. To control visual feedback, we employed shutter glasses that removed visual feedback during the reach, allowing us to measure trial-by-trial learning from error (termed error-sensitivity), and trial-by-trial decay of motor memory (termed forgetting). We found that the patients benefited significantly from the gradual protocol, improving their performance with respect to the abrupt protocol by exhibiting smaller errors during the exposure block, and producing larger aftereffects during the postexposure block. Trial-by-trial analysis suggested that this improvement was due to increased error-sensitivity in the gradual protocol. Therefore, cerebellar patients exhibited an improved ability to learn from error if they experienced those errors gradually. This improvement coincided with increased error-sensitivity and was present in both groups of subjects, suggesting that control of error-sensitivity may be spared despite cerebellar damage. PMID:26311179
Multijoint error compensation mediates unstable object control.
Cluff, Tyler; Manos, Aspasia; Lee, Timothy D; Balasubramaniam, Ramesh
2012-08-01
A key feature of skilled object control is the ability to correct performance errors. This process is not straightforward for unstable objects (e.g., inverted pendulum or "stick" balancing) because the mechanics of the object are sensitive to small control errors, which can lead to rapid performance changes. In this study, we have characterized joint recruitment and coordination processes in an unstable object control task. Our objective was to determine whether skill acquisition involves changes in the recruitment of individual joints or distributed error compensation. To address this problem, we monitored stick-balancing performance across four experimental sessions. We confirmed that subjects learned the task by showing an increase in the stability and length of balancing trials across training sessions. We demonstrated that motor learning led to the development of a multijoint error compensation strategy such that after training, subjects preferentially constrained joint angle variance that jeopardized task performance. The selective constraint of destabilizing joint angle variance was an important metric of motor learning. Finally, we performed a combined uncontrolled manifold-permutation analysis to ensure the variance structure was not confounded by differences in the variance of individual joint angles. We showed that reliance on multijoint error compensation increased, whereas individual joint variation (primarily at the wrist joint) decreased systematically with training. We propose a learning mechanism that is based on the accurate estimation of sensory states. PMID:22623491
Adaptive Inner-Loop Rover Control
NASA Technical Reports Server (NTRS)
Kulkarni, Nilesh; Ippolito, Corey; Krishnakumar, Kalmanje; Al-Ali, Khalid M.
2006-01-01
Adaptive control technology is developed for the inner-loop speed and steering control of the MAX Rover. MAX, a CMU developed rover, is a compact low-cost 4-wheel drive, 4-wheel steer (double Ackerman), high-clearance agile durable chassis, outfitted with sensors and electronics that make it ideally suited for supporting research relevant to intelligent teleoperation and as a low-cost autonomous robotic test bed and appliance. The design consists of a feedback linearization based controller with a proportional - integral (PI) feedback that is augmented by an online adaptive neural network. The adaptation law has guaranteed stability properties for safe operation. The control design is retrofit in nature so that it fits inside the outer-loop path planning algorithms. Successful hardware implementation of the controller is illustrated for several scenarios consisting of actuator failures and modeling errors in the nominal design.
Adaptive control of robotic manipulators
NASA Technical Reports Server (NTRS)
Seraji, H.
1987-01-01
The author presents a novel approach to adaptive control of manipulators to achieve trajectory tracking by the joint angles. The central concept in this approach is the utilization of the manipulator inverse as a feedforward controller. The desired trajectory is applied as an input to the feedforward controller which behaves as the inverse of the manipulator at any operating point; the controller output is used as the driving torque for the manipulator. The controller gains are then updated by an adaptation algorithm derived from MRAC (model reference adaptive control) theory to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal are also used to enhance closed-loop stability and to achieve faster adaptation. The proposed control scheme is computationally fast and does not require a priori knowledge of the complex dynamic model or the parameter values of the manipulator or the payload.
Adaptive neural control of spacecraft using control moment gyros
NASA Astrophysics Data System (ADS)
Leeghim, Henzeh; Kim, Donghoon
2015-03-01
An adaptive control technique is applied to reorient spacecraft with uncertainty using control moment gyros. A nonlinear quaternion feedback law is chosen as a baseline controller. An additional adaptive control input supported by neural networks can estimate and eliminate unknown terms adaptively. The normalized input neural networks are considered for reliable computation of the adaptive input. To prove the stability of the closed-loop dynamics with the control law, the Lyapunov stability theory is considered. Accordingly, the proposed approach results in the uniform ultimate boundedness in tracking error. For reorientation maneuvers, control moment gyros are utilized with a well-known singularity problem described in this work investigated by predicting one-step ahead singularity index. A momentum vector recovery approach using magnetic torquers is also introduced to evaluate the avoidance strategies indirectly. Finally, the suggested methods are demonstrated by numerical simulation studies.
Adaptive control strategies for flexible robotic arm
NASA Technical Reports Server (NTRS)
Bialasiewicz, Jan T.
1993-01-01
The motivation of this research came about when a neural network direct adaptive control scheme was applied to control the tip position of a flexible robotic arm. Satisfactory control performance was not attainable due to the inherent non-minimum phase characteristics of the flexible robotic arm tip. Most of the existing neural network control algorithms are based on the direct method and exhibit very high sensitivity if not unstable closed-loop behavior. Therefore a neural self-tuning control (NSTC) algorithm is developed and applied to this problem and showed promising results. Simulation results of the NSTC scheme and the conventional self-tuning (STR) control scheme are used to examine performance factors such as control tracking mean square error, estimation mean square error, transient response, and steady state response.
The importance of robust error control in data compression applications
NASA Technical Reports Server (NTRS)
Woolley, S. I.
1993-01-01
Data compression has become an increasingly popular option as advances in information technology have placed further demands on data storage capabilities. With compression ratios as high as 100:1 the benefits are clear; however, the inherent intolerance of many compression formats to error events should be given careful consideration. If we consider that efficiently compressed data will ideally contain no redundancy, then the introduction of a channel error must result in a change of understanding from that of the original source. While the prefix property of codes such as Huffman enables resynchronisation, this is not sufficient to arrest propagating errors in an adaptive environment. Arithmetic, Lempel-Ziv, discrete cosine transform (DCT) and fractal methods are similarly prone to error propagating behaviors. It is, therefore, essential that compression implementations provide sufficient combatant error control in order to maintain data integrity. Ideally, this control should be derived from a full understanding of the prevailing error mechanisms and their interaction with both the system configuration and the compression schemes in use.
Hellander, Andreas; Lawson, Michael J; Drawert, Brian; Petzold, Linda
2015-01-01
The efficiency of exact simulation methods for the reaction-diffusion master equation (RDME) is severely limited by the large number of diffusion events if the mesh is fine or if diffusion constants are large. Furthermore, inherent properties of exact kinetic-Monte Carlo simulation methods limit the efficiency of parallel implementations. Several approximate and hybrid methods have appeared that enable more efficient simulation of the RDME. A common feature to most of them is that they rely on splitting the system into its reaction and diffusion parts and updating them sequentially over a discrete timestep. This use of operator splitting enables more efficient simulation but it comes at the price of a temporal discretization error that depends on the size of the timestep. So far, existing methods have not attempted to estimate or control this error in a systematic manner. This makes the solvers hard to use for practitioners since they must guess an appropriate timestep. It also makes the solvers potentially less efficient than if the timesteps are adapted to control the error. Here, we derive estimates of the local error and propose a strategy to adaptively select the timestep when the RDME is simulated via a first order operator splitting. While the strategy is general and applicable to a wide range of approximate and hybrid methods, we exemplify it here by extending a previously published approximate method, the Diffusive Finite-State Projection (DFSP) method, to incorporate temporal adaptivity. PMID:26865735
NASA Astrophysics Data System (ADS)
Hellander, Andreas; Lawson, Michael J.; Drawert, Brian; Petzold, Linda
2014-06-01
The efficiency of exact simulation methods for the reaction-diffusion master equation (RDME) is severely limited by the large number of diffusion events if the mesh is fine or if diffusion constants are large. Furthermore, inherent properties of exact kinetic-Monte Carlo simulation methods limit the efficiency of parallel implementations. Several approximate and hybrid methods have appeared that enable more efficient simulation of the RDME. A common feature to most of them is that they rely on splitting the system into its reaction and diffusion parts and updating them sequentially over a discrete timestep. This use of operator splitting enables more efficient simulation but it comes at the price of a temporal discretization error that depends on the size of the timestep. So far, existing methods have not attempted to estimate or control this error in a systematic manner. This makes the solvers hard to use for practitioners since they must guess an appropriate timestep. It also makes the solvers potentially less efficient than if the timesteps were adapted to control the error. Here, we derive estimates of the local error and propose a strategy to adaptively select the timestep when the RDME is simulated via a first order operator splitting. While the strategy is general and applicable to a wide range of approximate and hybrid methods, we exemplify it here by extending a previously published approximate method, the diffusive finite-state projection (DFSP) method, to incorporate temporal adaptivity.
Hybrid adaptive control of a dragonfly model
NASA Astrophysics Data System (ADS)
Couceiro, Micael S.; Ferreira, Nuno M. F.; Machado, J. A. Tenreiro
2012-02-01
Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive ( HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive ( DA) method in terms of faster and improved tracking and parameter convergence.
Adaptive Wavefront Calibration and Control for the Gemini Planet Imager
Poyneer, L A; Veran, J
2007-02-02
Quasi-static errors in the science leg and internal AO flexure will be corrected. Wavefront control will adapt to current atmospheric conditions through Fourier modal gain optimization, or the prediction of atmospheric layers with Kalman filtering.
Error control coding for meteor burst channels
NASA Astrophysics Data System (ADS)
Frederick, T. J.; Belkerdid, M. A.; Georgiopoulos, M.
The performance of several error control coding schemes for a meteor burst channel is studied via analysis and simulation. These coding strategies are compared using the probability of successful transmission of a fixed size packet through a single burst as a performance measure. The coding methods are compared via simulation for several realizations of meteor burst. It is found that, based on complexity and probability of success, fixed-rate convolutional codes with soft decision Viterbi decoding provide better performance.
Efficient text segmentation and adaptive color error diffusion for text enhancement
NASA Astrophysics Data System (ADS)
Kwon, Jae-Hyun; Park, Tae-Yong; Kim, Yun-Tae; Cho, Yang-Ho; Ha, Yeong-Ho
2005-01-01
This paper proposes an adaptive error diffusion algorithm for text enhancement followed by an efficient text segmentation that uses the maximum gradient difference (MGD). The gradients are calculated along with scan lines, then the MGD values are filled within a local window to merge text segments. If the value is above a threshold, the pixel is considered as potential text. Isolated segments are then eliminated in a non-text region filtering process. After the text segmentation, a conventional error diffusion method is applied to the background, while edge enhancement error diffusion is used for the text. Since it is inevitable that visually objectionable artifacts are generated when using two different halftoning algorithms, gradual dilation is proposed to minimize the boundary artifacts in the segmented text blocks before halftoning. Sharpening based on the gradually dilated text region (GDTR) then prevents the printing of successive dots around the text region boundaries. The method is extended to halftone color images to sharpen the text regions. The proposed adaptive error diffusion algorithm involves color halftoning that controls the amount of edge enhancement using a general error filter. However, edge enhancement unfortunately produces color distortion, as edge enhancement and color difference are trade-offs. The multiplicative edge enhancement parameters are selected based on the amount of edge sharpening and color difference. Plus, an additional error factor is introduced to reduce the dot elimination artifact generated by the edge enhancement error diffusion. In experiments, the text of a scanned image was sharper when using the proposed algorithm than with conventional error diffusion without changing the background.
Efficient text segmentation and adaptive color error diffusion for text enhancement
NASA Astrophysics Data System (ADS)
Kwon, Jae-Hyun; Park, Tae-Yong; Kim, Yun-Tae; Cho, Yang-Ho; Ha, Yeong-Ho
2004-12-01
This paper proposes an adaptive error diffusion algorithm for text enhancement followed by an efficient text segmentation that uses the maximum gradient difference (MGD). The gradients are calculated along with scan lines, then the MGD values are filled within a local window to merge text segments. If the value is above a threshold, the pixel is considered as potential text. Isolated segments are then eliminated in a non-text region filtering process. After the text segmentation, a conventional error diffusion method is applied to the background, while edge enhancement error diffusion is used for the text. Since it is inevitable that visually objectionable artifacts are generated when using two different halftoning algorithms, gradual dilation is proposed to minimize the boundary artifacts in the segmented text blocks before halftoning. Sharpening based on the gradually dilated text region (GDTR) then prevents the printing of successive dots around the text region boundaries. The method is extended to halftone color images to sharpen the text regions. The proposed adaptive error diffusion algorithm involves color halftoning that controls the amount of edge enhancement using a general error filter. However, edge enhancement unfortunately produces color distortion, as edge enhancement and color difference are trade-offs. The multiplicative edge enhancement parameters are selected based on the amount of edge sharpening and color difference. Plus, an additional error factor is introduced to reduce the dot elimination artifact generated by the edge enhancement error diffusion. In experiments, the text of a scanned image was sharper when using the proposed algorithm than with conventional error diffusion without changing the background.
Aircraft adaptive learning control
NASA Technical Reports Server (NTRS)
Lee, P. S. T.; Vanlandingham, H. F.
1979-01-01
The optimal control theory of stochastic linear systems is discussed in terms of the advantages of distributed-control systems, and the control of randomly-sampled systems. An optimal solution to longitudinal control is derived and applied to the F-8 DFBW aircraft. A randomly-sampled linear process model with additive process and noise is developed.
Kinematic markers dissociate error correction from sensorimotor realignment during prism adaptation.
O'Shea, Jacinta; Gaveau, Valérie; Kandel, Matthieu; Koga, Kazuo; Susami, Kenji; Prablanc, Claude; Rossetti, Yves
2014-03-01
This study investigated the motor control mechanisms that enable healthy individuals to adapt their pointing movements during prism exposure to a rightward optical shift. In the prism adaptation literature, two processes are typically distinguished. Strategic motor adjustments are thought to drive the pattern of rapid endpoint error correction typically observed during the early stage of prism exposure. This is distinguished from so-called 'true sensorimotor realignment', normally measured with a different pointing task, at the end of prism exposure, which reveals a compensatory leftward 'prism after-effect'. Here, we tested whether each mode of motor compensation - strategic adjustments versus 'true sensorimotor realignment' - could be distinguished, by analyzing patterns of kinematic change during prism exposure. We hypothesized that fast feedforward versus slower feedback error corrective processes would map onto two distinct phases of the reach trajectory. Specifically, we predicted that feedforward adjustments would drive rapid compensation of the initial (acceleration) phase of the reach, resulting in the rapid reduction of endpoint errors typically observed early during prism exposure. By contrast, we expected visual-proprioceptive realignment to unfold more slowly and to reflect feedback influences during the terminal (deceleration) phase of the reach. The results confirmed these hypotheses. Rapid error reduction during the early stage of prism exposure was achieved by trial-by-trial adjustments of the motor plan, which were proportional to the endpoint error feedback from the previous trial. By contrast, compensation of the terminal reach phase unfolded slowly across the duration of prism exposure. Even after 100 trials of pointing through prisms, adaptation was incomplete, with participants continuing to exhibit a small rightward shift in both the reach endpoints and in the terminal phase of reach trajectories. Individual differences in the degree of
Zhou, Hui; Kunz, Thomas; Schwartz, Howard
2011-01-01
Traditional oscillators used in timing modules of CDMA and WiMAX base stations are large and expensive. Applying cheaper and smaller, albeit more inaccurate, oscillators in timing modules is an interesting research challenge. An adaptive control algorithm is presented to enhance the oscillators to meet the requirements of base stations during holdover mode. An oscillator frequency stability model is developed for the adaptive control algorithm. This model takes into account the control loop which creates the correction signal when the timing module is in locked mode. A recursive prediction error method is used to identify the system model parameters. Simulation results show that an oscillator enhanced by our adaptive control algorithm improves the oscillator performance significantly, compared with uncorrected oscillators. Our results also show the benefit of explicitly modeling the control loop. Finally, the cumulative time error upper bound of such enhanced oscillators is investigated analytically and comparison results between the analytical and simulated upper bound are provided. The results show that the analytical upper bound can serve as a practical guide for system designers. PMID:21244973
Hansen, M; Haugland, M K
2001-01-01
Adaptive restriction rules based on fuzzy logic have been developed to eliminate errors and to increase stimulation safety in the foot-drop correction application, specifically when using adaptive logic networks to provide a stimulation control signal based on neural activity recorded from peripheral sensory nerve branches. The fuzzy rules were designed to increase flexibility and offer easier customization, compared to earlier versions of restriction rules. The rules developed quantified the duration of swing and stance phases into states of accepting or rejecting new transitions, based on the cyclic nature of gait and statistics on the current gait patterns. The rules were easy to custom design for a specific application, using linguistic terms to model the actions of the rules. The rules were tested using pre-recorded gait data processed through a gait event detector and proved to reduce detection delay and the number of errors, compared to conventional rules. PMID:11601442
Direct adaptive control for nonlinear uncertain dynamical systems
NASA Astrophysics Data System (ADS)
Hayakawa, Tomohisa
; direct discrete-time adaptive control with guaranteed parameter error convergence; and hybrid adaptive control for nonlinear uncertain impulsive dynamical systems.
An integrated architecture of adaptive neural network control for dynamic systems
Ke, Liu; Tokar, R.; Mcvey, B.
1994-07-01
In this study, an integrated neural network control architecture for nonlinear dynamic systems is presented. Most of the recent emphasis in the neural network control field has no error feedback as the control input which rises the adaptation problem. The integrated architecture in this paper combines feed forward control and error feedback adaptive control using neural networks. The paper reveals the different internal functionality of these two kinds of neural network controllers for certain input styles, e.g., state feedback and error feedback. Feed forward neural network controllers with state feedback establish fixed control mappings which can not adapt when model uncertainties present. With error feedbacks, neural network controllers learn the slopes or the gains respecting to the error feedbacks, which are error driven adaptive control systems. The results demonstrate that the two kinds of control scheme can be combined to realize their individual advantages. Testing with disturbances added to the plant shows good tracking and adaptation.
Adaptive Control Of Remote Manipulator
NASA Technical Reports Server (NTRS)
Seraji, Homayoun
1989-01-01
Robotic control system causes remote manipulator to follow closely reference trajectory in Cartesian reference frame in work space, without resort to computationally intensive mathematical model of robot dynamics and without knowledge of robot and load parameters. System, derived from linear multivariable theory, uses relatively simple feedforward and feedback controllers with model-reference adaptive control.
Westendorff, Stephanie; Kuang, Shenbing; Taghizadeh, Bahareh; Donchin, Opher; Gail, Alexander
2015-04-01
Different error signals can induce sensorimotor adaptation during visually guided reaching, possibly evoking different neural adaptation mechanisms. Here we investigate reach adaptation induced by visual target errors without perturbing the actual or sensed hand position. We analyzed the spatial generalization of adaptation to target error to compare it with other known generalization patterns and simulated our results with a neural network model trained to minimize target error independent of prediction errors. Subjects reached to different peripheral visual targets and had to adapt to a sudden fixed-amplitude displacement ("jump") consistently occurring for only one of the reach targets. Subjects simultaneously had to perform contralateral unperturbed saccades, which rendered the reach target jump unnoticeable. As a result, subjects adapted by gradually decreasing reach errors and showed negative aftereffects for the perturbed reach target. Reach errors generalized to unperturbed targets according to a translational rather than rotational generalization pattern, but locally, not globally. More importantly, reach errors generalized asymmetrically with a skewed generalization function in the direction of the target jump. Our neural network model reproduced the skewed generalization after adaptation to target jump without having been explicitly trained to produce a specific generalization pattern. Our combined psychophysical and simulation results suggest that target jump adaptation in reaching can be explained by gradual updating of spatial motor goal representations in sensorimotor association networks, independent of learning induced by a prediction-error about the hand position. The simulations make testable predictions about the underlying changes in the tuning of sensorimotor neurons during target jump adaptation. PMID:25609106
Error Budget Analysis for an Adaptive Optics Optical Coherence Tomography System
Evans, Julia W.; Zawadzki, Robert J.; Jones, Steven M.; Olivier, Scot S.; Werner, John S.
2009-01-01
The combination of adaptive optics (AO) technology with optical coherence tomography (OCT) instrumentation for imaging the retina has proven to be a valuable tool for clinicians and researchers in understanding the healthy and diseased eye. The micrometer-isotropic resolution achieved by such a system allows imaging of the retina at a cellular level, however imaging of some cell types remains elusive. Improvement in contrast rather than resolution is needed and can be achieved through better AO correction of wavefront aberration. A common tool for assessing and ultimately improving AO system performance is the development of an error budget. Specifically, this is a list of the magnitude of the constituent residual errors of an optical system so that resources can be directed towards efficient performance improvement. Here we present an error budget developed for the UC Davis AO-OCT instrument indicating that bandwidth and controller errors are the limiting errors of our AO system, which should be corrected first to improve performance. We also discuss the scaling of error sources for different subjects and the need to improve the robustness of the system by addressing subject variability. PMID:19654784
Adaptive Control For Flexible Structures
NASA Technical Reports Server (NTRS)
Bayard, David S.; Ih, Che-Hang Charles; Wang, Shyh Jong
1988-01-01
Paper discusses ways to cope with measurement noise in adaptive control system for large, flexible structure in outer space. System generates control signals for torque and thrust actuators to turn all or parts of structure to desired orientations while suppressing torsional and other vibrations. Main result of paper is general theory for introduction of filters to suppress measurement noise while preserving stability.
Geometric view of adaptive optics control.
Wiberg, Donald M; Max, Claire E; Gavel, Donald T
2005-05-01
The objective of an astronomical adaptive optics control system is to minimize the residual wave-front error remaining on the science-object wave fronts after being compensated for atmospheric turbulence and telescope aberrations. Minimizing the mean square wave-front residual maximizes the Strehl ratio and the encircled energy in pointlike images and maximizes the contrast and resolution of extended images. We prove the separation principle of optimal control for application to adaptive optics so as to minimize the mean square wave-front residual. This shows that the residual wave-front error attributable to the control system can be decomposed into three independent terms that can be treated separately in design. The first term depends on the geometry of the wave-front sensor(s), the second term depends on the geometry of the deformable mirror(s), and the third term is a stochastic term that depends on the signal-to-noise ratio. The geometric view comes from understanding that the underlying quantity of interest, the wave-front phase surface, is really an infinite-dimensional vector within a Hilbert space and that this vector space is projected into subspaces we can control and measure by the deformable mirrors and wave-front sensors, respectively. When the control and estimation algorithms are optimal, the residual wave front is in a subspace that is the union of subspaces orthogonal to both of these projections. The method is general in that it applies both to conventional (on-axis, ground-layer conjugate) adaptive optics architectures and to more complicated multi-guide-star- and multiconjugate-layer architectures envisaged for future giant telescopes. We illustrate the approach by using a simple example that has been worked out previously [J. Opt. Soc. Am. A 73, 1171 (1983)] for a single-conjugate, static atmosphere case and follow up with a discussion of how it is extendable to general adaptive optics architectures. PMID:15898546
Finite-approximation-error-based discrete-time iterative adaptive dynamic programming.
Wei, Qinglai; Wang, Fei-Yue; Liu, Derong; Yang, Xiong
2014-12-01
In this paper, a new iterative adaptive dynamic programming (ADP) algorithm is developed to solve optimal control problems for infinite horizon discrete-time nonlinear systems with finite approximation errors. First, a new generalized value iteration algorithm of ADP is developed to make the iterative performance index function converge to the solution of the Hamilton-Jacobi-Bellman equation. The generalized value iteration algorithm permits an arbitrary positive semi-definite function to initialize it, which overcomes the disadvantage of traditional value iteration algorithms. When the iterative control law and iterative performance index function in each iteration cannot accurately be obtained, for the first time a new "design method of the convergence criteria" for the finite-approximation-error-based generalized value iteration algorithm is established. A suitable approximation error can be designed adaptively to make the iterative performance index function converge to a finite neighborhood of the optimal performance index function. Neural networks are used to implement the iterative ADP algorithm. Finally, two simulation examples are given to illustrate the performance of the developed method. PMID:25265640
Adaptive Control with Reference Model Modification
NASA Technical Reports Server (NTRS)
Stepanyan, Vahram; Krishnakumar, Kalmanje
2012-01-01
This paper presents a modification of the conventional model reference adaptive control (MRAC) architecture in order to improve transient performance of the input and output signals of uncertain systems. A simple modification of the reference model is proposed by feeding back the tracking error signal. It is shown that the proposed approach guarantees tracking of the given reference command and the reference control signal (one that would be designed if the system were known) not only asymptotically but also in transient. Moreover, it prevents generation of high frequency oscillations, which are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference commands of any magnitude from any initial position without re-tuning. The benefits of the method are demonstrated with a simulation example
Adaptive control based on retrospective cost optimization
NASA Technical Reports Server (NTRS)
Santillo, Mario A. (Inventor); Bernstein, Dennis S. (Inventor)
2012-01-01
A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.
Capitalization on Item Calibration Error in Adaptive Testing. Research Report 98-07.
ERIC Educational Resources Information Center
van der Linden, Wim J.; Glas, Cees A. W.
In adaptive testing, item selection is sequentially optimized during the test. Since the optimization takes place over a pool of items calibrated with estimation error, capitalization on these errors is likely to occur. How serious the consequences of this phenomenon are depends not only on the distribution of the estimation errors in the pool or…
Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model
NASA Technical Reports Server (NTRS)
Burken, John J.; Nguyen, Nhan T.; Griffin, Brian J.
2010-01-01
In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.
Eldred, Michael Scott; Subia, Samuel Ramirez; Neckels, David; Hopkins, Matthew Morgan; Notz, Patrick K.; Adams, Brian M.; Carnes, Brian; Wittwer, Jonathan W.; Bichon, Barron J.; Copps, Kevin D.
2006-10-01
This report documents the results for an FY06 ASC Algorithms Level 2 milestone combining error estimation and adaptivity, uncertainty quantification, and probabilistic design capabilities applied to the analysis and design of bistable MEMS. Through the use of error estimation and adaptive mesh refinement, solution verification can be performed in an automated and parameter-adaptive manner. The resulting uncertainty analysis and probabilistic design studies are shown to be more accurate, efficient, reliable, and convenient.
Model reference adaptive control of robots
NASA Technical Reports Server (NTRS)
Steinvorth, Rodrigo
1991-01-01
This project presents the results of controlling two types of robots using new Command Generator Tracker (CGT) based Direct Model Reference Adaptive Control (MRAC) algorithms. Two mathematical models were used to represent a single-link, flexible joint arm and a Unimation PUMA 560 arm; and these were then controlled in simulation using different MRAC algorithms. Special attention was given to the performance of the algorithms in the presence of sudden changes in the robot load. Previously used CGT based MRAC algorithms had several problems. The original algorithm that was developed guaranteed asymptotic stability only for almost strictly positive real (ASPR) plants. This condition is very restrictive, since most systems do not satisfy this assumption. Further developments to the algorithm led to an expansion of the number of plants that could be controlled, however, a steady state error was introduced in the response. These problems led to the introduction of some modifications to the algorithms so that they would be able to control a wider class of plants and at the same time would asymptotically track the reference model. This project presents the development of two algorithms that achieve the desired results and simulates the control of the two robots mentioned before. The results of the simulations are satisfactory and show that the problems stated above have been corrected in the new algorithms. In addition, the responses obtained show that the adaptively controlled processes are resistant to sudden changes in the load.
Westendorff, Stephanie; Kuang, Shenbing; Taghizadeh, Bahareh; Donchin, Opher
2015-01-01
Different error signals can induce sensorimotor adaptation during visually guided reaching, possibly evoking different neural adaptation mechanisms. Here we investigate reach adaptation induced by visual target errors without perturbing the actual or sensed hand position. We analyzed the spatial generalization of adaptation to target error to compare it with other known generalization patterns and simulated our results with a neural network model trained to minimize target error independent of prediction errors. Subjects reached to different peripheral visual targets and had to adapt to a sudden fixed-amplitude displacement (“jump”) consistently occurring for only one of the reach targets. Subjects simultaneously had to perform contralateral unperturbed saccades, which rendered the reach target jump unnoticeable. As a result, subjects adapted by gradually decreasing reach errors and showed negative aftereffects for the perturbed reach target. Reach errors generalized to unperturbed targets according to a translational rather than rotational generalization pattern, but locally, not globally. More importantly, reach errors generalized asymmetrically with a skewed generalization function in the direction of the target jump. Our neural network model reproduced the skewed generalization after adaptation to target jump without having been explicitly trained to produce a specific generalization pattern. Our combined psychophysical and simulation results suggest that target jump adaptation in reaching can be explained by gradual updating of spatial motor goal representations in sensorimotor association networks, independent of learning induced by a prediction-error about the hand position. The simulations make testable predictions about the underlying changes in the tuning of sensorimotor neurons during target jump adaptation. PMID:25609106
Robust adaptive tracking control for nonholonomic mobile manipulator with uncertainties.
Peng, Jinzhu; Yu, Jie; Wang, Jie
2014-07-01
In this paper, mobile manipulator is divided into two subsystems, that is, nonholonomic mobile platform subsystem and holonomic manipulator subsystem. First, the kinematic controller of the mobile platform is derived to obtain a desired velocity. Second, regarding the coupling between the two subsystems as disturbances, Lyapunov functions of the two subsystems are designed respectively. Third, a robust adaptive tracking controller is proposed to deal with the unknown upper bounds of parameter uncertainties and disturbances. According to the Lyapunov stability theory, the derived robust adaptive controller guarantees global stability of the closed-loop system, and the tracking errors and adaptive coefficient errors are all bounded. Finally, simulation results show that the proposed robust adaptive tracking controller for nonholonomic mobile manipulator is effective and has good tracking capacity. PMID:24917071
The reduced order model problem in distributed parameter systems adaptive identification and control
NASA Technical Reports Server (NTRS)
Johnson, C. R., Jr.
1980-01-01
The research concerning the reduced order model problem in distributed parameter systems is reported. The adaptive control strategy was chosen for investigation in the annular momentum control device. It is noted, that if there is no observation spill over, and no model errors, an indirect adaptive control strategy can be globally stable. Recent publications concerning adaptive control are included.
Johnson, Dominic D P; Blumstein, Daniel T; Fowler, James H; Haselton, Martie G
2013-08-01
Counterintuitively, biases in behavior or cognition can improve decision making. Under conditions of uncertainty and asymmetric costs of 'false-positive' and 'false-negative' errors, biases can lead to mistakes in one direction but - in so doing - steer us away from more costly mistakes in the other direction. For example, we sometimes think sticks are snakes (which is harmless), but rarely that snakes are sticks (which can be deadly). We suggest that 'error management' biases: (i) have been independently identified by multiple interdisciplinary studies, suggesting the phenomenon is robust across domains, disciplines, and methodologies; (ii) represent a general feature of life, with common sources of variation; and (iii) offer an explanation, in error management theory (EMT), for the evolution of cognitive biases as the best way to manage errors under cognitive and evolutionary constraints. PMID:23787087
On fractional order composite model reference adaptive control
NASA Astrophysics Data System (ADS)
Wei, Yiheng; Sun, Zhenyuan; Hu, Yangsheng; Wang, Yong
2016-08-01
This paper presents a novel composite model reference adaptive control approach for a class of fractional order linear systems with unknown constant parameters. The method is extended from the model reference adaptive control. The parameter estimation error of our method depends on both the tracking error and the prediction error, whereas the existing method only depends on the tracking error, which makes our method has better transient performance in the sense of generating smooth system output. By the aid of the continuous frequency distributed model, stability of the proposed approach is established in the Lyapunov sense. Furthermore, the convergence property of the model parameters estimation is presented, on the premise that the closed-loop control system is stable. Finally, numerical simulation examples are given to demonstrate the effectiveness of the proposed schemes.
Adaptable state based control system
NASA Technical Reports Server (NTRS)
Rasmussen, Robert D. (Inventor); Dvorak, Daniel L. (Inventor); Gostelow, Kim P. (Inventor); Starbird, Thomas W. (Inventor); Gat, Erann (Inventor); Chien, Steve Ankuo (Inventor); Keller, Robert M. (Inventor)
2004-01-01
An autonomous controller, comprised of a state knowledge manager, a control executor, hardware proxies and a statistical estimator collaborates with a goal elaborator, with which it shares common models of the behavior of the system and the controller. The elaborator uses the common models to generate from temporally indeterminate sets of goals, executable goals to be executed by the controller. The controller may be updated to operate in a different system or environment than that for which it was originally designed by the replacement of shared statistical models and by the instantiation of a new set of state variable objects derived from a state variable class. The adaptation of the controller does not require substantial modification of the goal elaborator for its application to the new system or environment.
Persistent residual errors in motor adaptation tasks: reversion to baseline and exploratory escape.
Vaswani, Pavan A; Shmuelof, Lior; Haith, Adrian M; Delnicki, Raymond J; Huang, Vincent S; Mazzoni, Pietro; Shadmehr, Reza; Krakauer, John W
2015-04-29
When movements are perturbed in adaptation tasks, humans and other animals show incomplete compensation, tolerating small but sustained residual errors that persist despite repeated trials. State-space models explain this residual asymptotic error as interplay between learning from error and reversion to baseline, a form of forgetting. Previous work using zero-error-clamp trials has shown that reversion to baseline is not obligatory and can be overcome by manipulating feedback. We posited that novel error-clamp trials, in which feedback is constrained but has nonzero error and variance, might serve as a contextual cue for recruitment of other learning mechanisms that would then close the residual error. When error clamps were nonzero and had zero variance, human subjects changed their learning policy, using exploration in response to the residual error, despite their willingness to sustain such an error during the training block. In contrast, when the distribution of feedback in clamp trials was naturalistic, with persistent mean error but also with variance, a state-space model accounted for behavior in clamps, even in the absence of task success. Therefore, when the distribution of errors matched those during training, state-space models captured behavior during both adaptation and error-clamp trials because error-based learning dominated; when the distribution of feedback was altered, other forms of learning were triggered that did not follow the state-space model dynamics exhibited during training. The residual error during adaptation appears attributable to an error-dependent learning process that has the property of reversion toward baseline and that can suppress other forms of learning. PMID:25926471
Persistent Residual Errors in Motor Adaptation Tasks: Reversion to Baseline and Exploratory Escape
Shmuelof, Lior; Haith, Adrian M.; Delnicki, Raymond J.; Huang, Vincent S.; Mazzoni, Pietro; Shadmehr, Reza; Krakauer, John W.
2015-01-01
When movements are perturbed in adaptation tasks, humans and other animals show incomplete compensation, tolerating small but sustained residual errors that persist despite repeated trials. State-space models explain this residual asymptotic error as interplay between learning from error and reversion to baseline, a form of forgetting. Previous work using zero-error-clamp trials has shown that reversion to baseline is not obligatory and can be overcome by manipulating feedback. We posited that novel error-clamp trials, in which feedback is constrained but has nonzero error and variance, might serve as a contextual cue for recruitment of other learning mechanisms that would then close the residual error. When error clamps were nonzero and had zero variance, human subjects changed their learning policy, using exploration in response to the residual error, despite their willingness to sustain such an error during the training block. In contrast, when the distribution of feedback in clamp trials was naturalistic, with persistent mean error but also with variance, a state-space model accounted for behavior in clamps, even in the absence of task success. Therefore, when the distribution of errors matched those during training, state-space models captured behavior during both adaptation and error-clamp trials because error-based learning dominated; when the distribution of feedback was altered, other forms of learning were triggered that did not follow the state-space model dynamics exhibited during training. The residual error during adaptation appears attributable to an error-dependent learning process that has the property of reversion toward baseline and that can suppress other forms of learning. PMID:25926471
Method For Model-Reference Adaptive Control
NASA Technical Reports Server (NTRS)
Seraji, Homayoun
1990-01-01
Relatively simple method of model-reference adaptive control (MRAC) developed from two prior classes of MRAC techniques: signal-synthesis method and parameter-adaption method. Incorporated into unified theory, which yields more general adaptation scheme.
An error control system with multiple-stage forward error corrections
NASA Technical Reports Server (NTRS)
Takata, Toyoo; Fujiwara, Toru; Kasami, Tadao; Lin, Shu
1990-01-01
A robust error-control coding system is presented. This system is a cascaded FEC (forward error control) scheme supported by parity retransmissions for further error correction in the erroneous data words. The error performance and throughput efficiency of the system are analyzed. Two specific examples of the error-control system are studied. The first example does not use an inner code, and the outer code, which is not interleaved, is a shortened code of the NASA standard RS code over GF(28). The second example, as proposed for NASA, uses the same shortened RS code as the base outer code C2, except that it is interleaved to a depth of 2. It is shown that both examples provide high reliability and throughput efficiency even for high channel bit-error rates in the range of 0.01.
Adaptive feed-forward loop connection based on error signal
NASA Astrophysics Data System (ADS)
Hidaka, Koichi
2005-12-01
In this paper, we investigate effect of changing the connection of feed-forward loop based on error signal. Our motivation of this work is solution to progress of human skill. For the skill model, we study a human simple action such as arm motion. Many models that describe the human arm dynamics have been proposed in recent year. While one type does not need an inverse model of human dynamics, the system based on the model does not include feed-forward loop. On the other hand, another type model has a feed-forward loop and feedback loop systems. This type assumes feed-forward element includes an internal model by repeating action or training and this loop progress our skill. Then we usually have to exercise to get a good performance. This says that we design the internal motion model by training and we move on prediction for motion. Under the assumption, Kawato model is well known. The model proposed that learning of feed-forward element is promoted in brain so that the error of feedback loop decreases. Furthermore, we assume the connections in feedback loop and feed-forward loop are changed. We show numerical simulations and consider that the position error given by our vision changes the skill element and we confirm that the position error is the one of the estimate function for the improvement in our skill.
An hp-adaptivity and error estimation for hyperbolic conservation laws
NASA Technical Reports Server (NTRS)
Bey, Kim S.
1995-01-01
This paper presents an hp-adaptive discontinuous Galerkin method for linear hyperbolic conservation laws. A priori and a posteriori error estimates are derived in mesh-dependent norms which reflect the dependence of the approximate solution on the element size (h) and the degree (p) of the local polynomial approximation. The a posteriori error estimate, based on the element residual method, provides bounds on the actual global error in the approximate solution. The adaptive strategy is designed to deliver an approximate solution with the specified level of error in three steps. The a posteriori estimate is used to assess the accuracy of a given approximate solution and the a priori estimate is used to predict the mesh refinements and polynomial enrichment needed to deliver the desired solution. Numerical examples demonstrate the reliability of the a posteriori error estimates and the effectiveness of the hp-adaptive strategy.
Adaptive Force Control in Compliant Motion
NASA Technical Reports Server (NTRS)
Seraji, H.
1994-01-01
This paper addresses the problem of controlling a manipulator in compliant motion while in contact with an environment having an unknown stiffness. Two classes of solutions are discussed: adaptive admittance control and adaptive compliance control. In both admittance and compliance control schemes, compensator adaptation is used to ensure a stable and uniform system performance.
Adaptive support vector regression for UAV flight control.
Shin, Jongho; Jin Kim, H; Kim, Youdan
2011-01-01
This paper explores an application of support vector regression for adaptive control of an unmanned aerial vehicle (UAV). Unlike neural networks, support vector regression (SVR) generates global solutions, because SVR basically solves quadratic programming (QP) problems. With this advantage, the input-output feedback-linearized inverse dynamic model and the compensation term for the inversion error are identified off-line, which we call I-SVR (inversion SVR) and C-SVR (compensation SVR), respectively. In order to compensate for the inversion error and the unexpected uncertainty, an online adaptation algorithm for the C-SVR is proposed. Then, the stability of the overall error dynamics is analyzed by the uniformly ultimately bounded property in the nonlinear system theory. In order to validate the effectiveness of the proposed adaptive controller, numerical simulations are performed on the UAV model. PMID:20970303
Keck adaptive optics: control subsystem
Brase, J.M.; An, J.; Avicola, K.
1996-03-08
Adaptive optics on the Keck 10 meter telescope will provide an unprecedented level of capability in high resolution ground based astronomical imaging. The system is designed to provide near diffraction limited imaging performance with Strehl {gt} 0.3 n median Keck seeing of r0 = 25 cm, T =10 msec at 500 nm wavelength. The system will be equipped with a 20 watt sodium laser guide star to provide nearly full sky coverage. The wavefront control subsystem is responsible for wavefront sensing and the control of the tip-tilt and deformable mirrors which actively correct atmospheric turbulence. The spatial sampling interval for the wavefront sensor and deformable mirror is de=0.56 m which gives us 349 actuators and 244 subapertures. This paper summarizes the wavefront control system and discusses particular issues in designing a wavefront controller for the Keck telescope.
Experimental investigation of adaptive control of a parallel manipulator
NASA Technical Reports Server (NTRS)
Nguyen, Charles C.; Antrazi, Sami S.
1992-01-01
The implementation of a joint-space adaptive control scheme used to control non-compliant motion of a Stewart Platform-based Manipulator (SPBM) is presented. The SPBM is used in a facility called the Hardware Real-Time Emulator (HRTE) developed at Goddard Space Flight Center to emulate space operations. The SPBM is comprised of two platforms and six linear actuators driven by DC motors, and possesses six degrees of freedom. The report briefly reviews the development of the adaptive control scheme which is composed of proportional-derivative (PD) controllers whose gains are adjusted by an adaptation law driven by the errors between the desired and actual trajectories of the SPBM actuator lengths. The derivation of the adaptation law is based on the concept of model reference adaptive control (MRAC) and Lyapunov direct method under the assumption that SPBM motion is slow as compared to the controller adaptation rate. An experimental study is conducted to evaluate the performance of the adaptive control scheme implemented to control the SPBM to track a vertical and circular paths under step changes in payload. Experimental results show that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.
A Java Applet for Illustrating Internet Error Control
ERIC Educational Resources Information Center
Holliday, Mark A.
2004-01-01
This paper discusses the author's experiences developing a Java applet that illustrates how error control is implemented in the Transmission Control Protocol (TCP). One section discusses the concepts which the TCP error control Java applet is intended to convey, while the nature of the Java applet is covered in another section. The author…
Evaluation and control of spatial frequency errors in reflective telescopes
NASA Astrophysics Data System (ADS)
Zhang, Xuejun; Zeng, Xuefeng; Hu, Haixiang; Zheng, Ligong
2015-08-01
In this paper, the influence on the image quality of manufacturing residual errors was studied. By analyzing the statistical distribution characteristics of the residual errors and their effects on PSF and MTF, we divided those errors into low, middle and high frequency domains using the unit "cycles per aperture". Two types of mid-frequency errors, algorithm intrinsic and tool path induced were analyzed. Control methods in current deterministic polishing process, such as MRF or IBF were presented.
Intelligent Engine Systems: Adaptive Control
NASA Technical Reports Server (NTRS)
Gibson, Nathan
2008-01-01
We have studied the application of the baseline Model Predictive Control (MPC) algorithm to the control of main fuel flow rate (WF36), variable bleed valve (AE24) and variable stator vane (STP25) control of a simulated high-bypass turbofan engine. Using reference trajectories for thrust and turbine inlet temperature (T41) generated by a simulated new engine, we have examined MPC for tracking these two reference outputs while controlling a deteriorated engine. We have examined the results of MPC control for six different transients: two idle-to-takeoff transients at sea level static (SLS) conditions, one takeoff-to-idle transient at SLS, a Bode power command and reverse Bode power command at 20,000 ft/Mach 0.5, and a reverse Bode transient at 35,000 ft/Mach 0.84. For all cases, our primary focus was on the computational effort required by MPC for varying MPC update rates, control horizons, and prediction horizons. We have also considered the effects of these MPC parameters on the performance of the control, with special emphasis on the thrust tracking error, the peak T41, and the sizes of violations of the constraints on the problem, primarily the booster stall margin limit, which for most cases is the lone constraint that is violated with any frequency.
Alavandar, Srinivasan; Nigam, M J
2009-10-01
Control of an industrial robot includes nonlinearities, uncertainties and external perturbations that should be considered in the design of control laws. In this paper, some new hybrid adaptive neuro-fuzzy control algorithms (ANFIS) have been proposed for manipulator control with uncertainties. These hybrid controllers consist of adaptive neuro-fuzzy controllers and conventional controllers. The outputs of these controllers are applied to produce the final actuation signal based on current position and velocity errors. Numerical simulation using the dynamic model of six DOF puma robot arm with uncertainties shows the effectiveness of the approach in trajectory tracking problems. Performance indices of RMS error, maximum error are used for comparison. It is observed that the hybrid adaptive neuro-fuzzy controllers perform better than only conventional/adaptive controllers and in particular hybrid controller structure consisting of adaptive neuro-fuzzy controller and critically damped inverse dynamics controller. PMID:19523623
Attitude control with realization of linear error dynamics
NASA Technical Reports Server (NTRS)
Paielli, Russell A.; Bach, Ralph E.
1993-01-01
An attitude control law is derived to realize linear unforced error dynamics with the attitude error defined in terms of rotation group algebra (rather than vector algebra). Euler parameters are used in the rotational dynamics model because they are globally nonsingular, but only the minimal three Euler parameters are used in the error dynamics model because they have no nonlinear mathematical constraints to prevent the realization of linear error dynamics. The control law is singular only when the attitude error angle is exactly pi rad about any eigenaxis, and a simple intuitive modification at the singularity allows the control law to be used globally. The forced error dynamics are nonlinear but stable. Numerical simulation tests show that the control law performs robustly for both initial attitude acquisition and attitude control.
Error estimation and adaptive mesh refinement for parallel analysis of shell structures
NASA Technical Reports Server (NTRS)
Keating, Scott C.; Felippa, Carlos A.; Park, K. C.
1994-01-01
The formulation and application of element-level, element-independent error indicators is investigated. This research culminates in the development of an error indicator formulation which is derived based on the projection of element deformation onto the intrinsic element displacement modes. The qualifier 'element-level' means that no information from adjacent elements is used for error estimation. This property is ideally suited for obtaining error values and driving adaptive mesh refinements on parallel computers where access to neighboring elements residing on different processors may incur significant overhead. In addition such estimators are insensitive to the presence of physical interfaces and junctures. An error indicator qualifies as 'element-independent' when only visible quantities such as element stiffness and nodal displacements are used to quantify error. Error evaluation at the element level and element independence for the error indicator are highly desired properties for computing error in production-level finite element codes. Four element-level error indicators have been constructed. Two of the indicators are based on variational formulation of the element stiffness and are element-dependent. Their derivations are retained for developmental purposes. The second two indicators mimic and exceed the first two in performance but require no special formulation of the element stiffness mesh refinement which we demonstrate for two dimensional plane stress problems. The parallelizing of substructures and adaptive mesh refinement is discussed and the final error indicator using two-dimensional plane-stress and three-dimensional shell problems is demonstrated.
Short-term adaptation of the VOR: non-retinal-slip error signals and saccade substitution
NASA Technical Reports Server (NTRS)
Eggers, Sscott D Z.; De Pennington, Nick; Walker, Mark F.; Shelhamer, Mark; Zee, David S.
2003-01-01
We studied short-term (30 min) adaptation of the vestibulo-ocular reflex (VOR) in five normal humans using a "position error" stimulus without retinal image motion. Both before and after adaptation a velocity gain (peak slow-phase eye velocity/peak head velocity) and a position gain (total eye movement during chair rotation/amplitude of chair motion) were measured in darkness using search coils. The vestibular stimulus was a brief ( approximately 700 ms), 15 degrees chair rotation in darkness (peak velocity 43 degrees /s). To elicit adaptation, a straight-ahead fixation target disappeared during chair movement and when the chair stopped the target reappeared at a new location in front of the subject for gain-decrease (x0) adaptation, or 10 degrees opposite to chair motion for gain-increase (x1.67) adaptation. This position-error stimulus was effective at inducing VOR adaptation, though for gain-increase adaptation the primary strategy was to substitute augmenting saccades during rotation while for gain-decrease adaptation both corrective saccades and a decrease in slow-phase velocity occurred. Finally, the presence of the position-error signal alone, at the end of head rotation, without any attempt to fix upon it, was not sufficient to induce adaptation. Adaptation did occur, however, if the subject did make a saccade to the target after head rotation, or even if the subject paid attention to the new location of the target without actually looking at it.
Adaptive control system for pulsed megawatt klystrons
Bolie, Victor W.
1992-01-01
The invention provides an arrangement for reducing waveform errors such as errors in phase or amplitude in output pulses produced by pulsed power output devices such as klystrons by generating an error voltage representing the extent of error still present in the trailing edge of the previous output pulse, using the error voltage to provide a stored control voltage, and applying the stored control voltage to the pulsed power output device to limit the extent of error in the leading edge of the next output pulse.
Adaptive Flight Control for Aircraft Safety Enhancements
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Gregory, Irene M.; Joshi, Suresh M.
2008-01-01
This poster presents the current adaptive control research being conducted at NASA ARC and LaRC in support of the Integrated Resilient Aircraft Control (IRAC) project. The technique "Approximate Stability Margin Analysis of Hybrid Direct-Indirect Adaptive Control" has been developed at NASA ARC to address the needs for stability margin metrics for adaptive control that potentially enables future V&V of adaptive systems. The technique "Direct Adaptive Control With Unknown Actuator Failures" is developed at NASA LaRC to deal with unknown actuator failures. The technique "Adaptive Control with Adaptive Pilot Element" is being researched at NASA LaRC to investigate the effects of pilot interactions with adaptive flight control that can have implications of stability and performance.
Missile guidance law design using adaptive cerebellar model articulation controller.
Lin, Chih-Min; Peng, Ya-Fu
2005-05-01
An adaptive cerebellar model articulation controller (CMAC) is proposed for command to line-of-sight (CLOS) missile guidance law design. In this design, the three-dimensional (3-D) CLOS guidance problem is formulated as a tracking problem of a time-varying nonlinear system. The adaptive CMAC control system is comprised of a CMAC and a compensation controller. The CMAC control is used to imitate a feedback linearization control law and the compensation controller is utilized to compensate the difference between the feedback linearization control law and the CMAC control. The online adaptive law is derived based on the Lyapunov stability theorem to learn the weights of receptive-field basis functions in CMAC control. In addition, in order to relax the requirement of approximation error bound, an estimation law is derived to estimate the error bound. Then the adaptive CMAC control system is designed to achieve satisfactory tracking performance. Simulation results for different engagement scenarios illustrate the validity of the proposed adaptive CMAC-based guidance law. PMID:15940993
Model reference adaptive attitude control of spacecraft using reaction wheels
NASA Technical Reports Server (NTRS)
Singh, Sahjendra N.
1986-01-01
A nonlinear model reference adaptive control law for large angle rotational maneuvers of spacecraft using reaction wheels in the presence of uncertainty is presented. The derivation of control law does not require any information on the values of the system parameters and the disturbance torques acting on the spacecraft. The controller includes a dynamic system in the feedback path. The control law is a nonlinear function of the attitude error, the rate of the attitude error, and the compensator state. Simulation results are prsented to show that large angle rotational maneuvers can be performed in spite of the uncertainty in the system.
Adjoint-Based, Three-Dimensional Error Prediction and Grid Adaptation
NASA Technical Reports Server (NTRS)
Park, Michael A.
2002-01-01
Engineering computational fluid dynamics (CFD) analysis and design applications focus on output functions (e.g., lift, drag). Errors in these output functions are generally unknown and conservatively accurate solutions may be computed. Computable error estimates can offer the possibility to minimize computational work for a prescribed error tolerance. Such an estimate can be computed by solving the flow equations and the linear adjoint problem for the functional of interest. The computational mesh can be modified to minimize the uncertainty of a computed error estimate. This robust mesh-adaptation procedure automatically terminates when the simulation is within a user specified error tolerance. This procedure for estimating and adapting to error in a functional is demonstrated for three-dimensional Euler problems. An adaptive mesh procedure that links to a Computer Aided Design (CAD) surface representation is demonstrated for wing, wing-body, and extruded high lift airfoil configurations. The error estimation and adaptation procedure yielded corrected functions that are as accurate as functions calculated on uniformly refined grids with ten times as many grid points.
NASA Astrophysics Data System (ADS)
Wu, Heng
2000-10-01
In this thesis, an a-posteriori error estimator is presented and employed for solving viscous incompressible flow problems. In an effort to detect local flow features, such as vortices and separation, and to resolve flow details precisely, a velocity angle error estimator e theta which is based on the spatial derivative of velocity direction fields is designed and constructed. The a-posteriori error estimator corresponds to the antisymmetric part of the deformation-rate-tensor, and it is sensitive to the second derivative of the velocity angle field. Rationality discussions reveal that the velocity angle error estimator is a curvature error estimator, and its value reflects the accuracy of streamline curves. It is also found that the velocity angle error estimator contains the nonlinear convective term of the Navier-Stokes equations, and it identifies and computes the direction difference when the convective acceleration direction and the flow velocity direction have a disparity. Through benchmarking computed variables with the analytic solution of Kovasznay flow or the finest grid of cavity flow, it is demonstrated that the velocity angle error estimator has a better performance than the strain error estimator. The benchmarking work also shows that the computed profile obtained by using etheta can achieve the best matching outcome with the true theta field, and that it is asymptotic to the true theta variation field, with a promise of fewer unknowns. Unstructured grids are adapted by employing local cell division as well as unrefinement of transition cells. Using element class and node class can efficiently construct a hierarchical data structure which provides cell and node inter-reference at each adaptive level. Employing element pointers and node pointers can dynamically maintain the connection of adjacent elements and adjacent nodes, and thus avoids time-consuming search processes. The adaptive scheme is applied to viscous incompressible flow at different
Adaptive error covariances estimation methods for ensemble Kalman filters
Zhen, Yicun; Harlim, John
2015-08-01
This paper presents a computationally fast algorithm for estimating, both, the system and observation noise covariances of nonlinear dynamics, that can be used in an ensemble Kalman filtering framework. The new method is a modification of Belanger's recursive method, to avoid an expensive computational cost in inverting error covariance matrices of product of innovation processes of different lags when the number of observations becomes large. When we use only product of innovation processes up to one-lag, the computational cost is indeed comparable to a recently proposed method by Berry–Sauer's. However, our method is more flexible since it allows for using information from product of innovation processes of more than one-lag. Extensive numerical comparisons between the proposed method and both the original Belanger's and Berry–Sauer's schemes are shown in various examples, ranging from low-dimensional linear and nonlinear systems of SDEs and 40-dimensional stochastically forced Lorenz-96 model. Our numerical results suggest that the proposed scheme is as accurate as the original Belanger's scheme on low-dimensional problems and has a wider range of more accurate estimates compared to Berry–Sauer's method on L-96 example.
Robust adaptive control for Unmanned Aerial Vehicles
NASA Astrophysics Data System (ADS)
Kahveci, Nazli E.
anti-windup compensation. Our analysis on the indirect adaptive scheme reveals that the perturbation terms due to parameter errors do not cause any unbounded signals in the closed-loop. The stability of the adaptive system is established, and the properties of the proposed control scheme are demonstrated through simulations on a UAV model with input magnitude saturation constraints. The robust adaptive control design is further developed to extend our results to rate-saturated systems.
Designing to Control Flight Crew Errors
NASA Technical Reports Server (NTRS)
Schutte, Paul C.; Willshire, Kelli F.
1997-01-01
It is widely accepted that human error is a major contributing factor in aircraft accidents. There has been a significant amount of research in why these errors occurred, and many reports state that the design of flight deck can actually dispose humans to err. This research has led to the call for changes in design according to human factors and human-centered principles. The National Aeronautics and Space Administration's (NASA) Langley Research Center has initiated an effort to design a human-centered flight deck from a clean slate (i.e., without constraints of existing designs.) The effort will be based on recent research in human-centered design philosophy and mission management categories. This design will match the human's model of the mission and function of the aircraft to reduce unnatural or non-intuitive interfaces. The product of this effort will be a flight deck design description, including training and procedures, and a cross reference or paper trail back to design hypotheses, and an evaluation of the design. The present paper will discuss the philosophy, process, and status of this design effort.
Servo control booster system for minimizing following error
Wise, William L.
1985-01-01
A closed-loop feedback-controlled servo system is disclosed which reduces command-to-response error to the system's position feedback resolution least increment, .DELTA.S.sub.R, on a continuous real-time basis for all operating speeds. The servo system employs a second position feedback control loop on a by exception basis, when the command-to-response error .gtoreq..DELTA.S.sub.R, to produce precise position correction signals. When the command-to-response error is less than .DELTA.S.sub.R, control automatically reverts to conventional control means as the second position feedback control loop is disconnected, becoming transparent to conventional servo control means. By operating the second unique position feedback control loop used herein at the appropriate clocking rate, command-to-response error may be reduced to the position feedback resolution least increment. The present system may be utilized in combination with a tachometer loop for increased stability.
Novel Hybrid Adaptive Controller for Manipulation in Complex Perturbation Environments
Smith, Alex M. C.; Yang, Chenguang; Ma, Hongbin; Culverhouse, Phil; Cangelosi, Angelo; Burdet, Etienne
2015-01-01
In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing. PMID:26029916
Novel hybrid adaptive controller for manipulation in complex perturbation environments.
Smith, Alex M C; Yang, Chenguang; Ma, Hongbin; Culverhouse, Phil; Cangelosi, Angelo; Burdet, Etienne
2015-01-01
In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing. PMID:26029916
Yang, Yana; Hua, Changchun; Guan, Xinping
2016-03-01
Due to the cognitive limitations of the human operator and lack of complete information about the remote environment, the work performance of such teleoperation systems cannot be guaranteed in most cases. However, some practical tasks conducted by the teleoperation system require high performances, such as tele-surgery needs satisfactory high speed and more precision control results to guarantee patient' health status. To obtain some satisfactory performances, the error constrained control is employed by applying the barrier Lyapunov function (BLF). With the constrained synchronization errors, some high performances, such as, high convergence speed, small overshoot, and an arbitrarily predefined small residual constrained synchronization error can be achieved simultaneously. Nevertheless, like many classical control schemes only the asymptotic/exponential convergence, i.e., the synchronization errors converge to zero as time goes infinity can be achieved with the error constrained control. It is clear that finite time convergence is more desirable. To obtain a finite-time synchronization performance, the terminal sliding mode (TSM)-based finite time control method is developed for teleoperation system with position error constrained in this paper. First, a new nonsingular fast terminal sliding mode (NFTSM) surface with new transformed synchronization errors is proposed. Second, adaptive neural network system is applied for dealing with the system uncertainties and the external disturbances. Third, the BLF is applied to prove the stability and the nonviolation of the synchronization errors constraints. Finally, some comparisons are conducted in simulation and experiment results are also presented to show the effectiveness of the proposed method. PMID:25823053
Online Error Reporting for Managing Quality Control Within Radiology.
Golnari, Pedram; Forsberg, Daniel; Rosipko, Beverly; Sunshine, Jeffrey L
2016-06-01
Information technology systems within health care, such as picture archiving and communication system (PACS) in radiology, can have a positive impact on production but can also risk compromising quality. The widespread use of PACS has removed the previous feedback loop between radiologists and technologists. Instead of direct communication of quality discrepancies found for an examination, the radiologist submitted a paper-based quality-control report. A web-based issue-reporting tool can help restore some of the feedback loop and also provide possibilities for more detailed analysis of submitted errors. The purpose of this study was to evaluate the hypothesis that data from use of an online error reporting software for quality control can focus our efforts within our department. For the 372,258 radiologic examinations conducted during the 6-month period study, 930 errors (390 exam protocol, 390 exam validation, and 150 exam technique) were submitted, corresponding to an error rate of 0.25 %. Within the category exam protocol, technologist documentation had the highest number of submitted errors in ultrasonography (77 errors [44 %]), while imaging protocol errors were the highest subtype error for computed tomography modality (35 errors [18 %]). Positioning and incorrect accession had the highest errors in the exam technique and exam validation error category, respectively, for nearly all of the modalities. An error rate less than 1 % could signify a system with a very high quality; however, a more likely explanation is that not all errors were detected or reported. Furthermore, staff reception of the error reporting system could also affect the reporting rate. PMID:26510753
Dual-arm manipulators with adaptive control
NASA Technical Reports Server (NTRS)
Seraji, Homayoun (Inventor)
1991-01-01
The described and improved multi-arm invention of this application presents three strategies for adaptive control of cooperative multi-arm robots which coordinate control over a common load. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through a load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions; while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are compensated for by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. Circuits in the adaptive feedback and feedforward controllers are varied by novel adaptation laws.
Simple method for model reference adaptive control
NASA Technical Reports Server (NTRS)
Seraji, H.
1989-01-01
A simple method is presented for combined signal synthesis and parameter adaptation within the framework of model reference adaptive control theory. The results are obtained using a simple derivation based on an improved Liapunov function.
Two hybrid ARQ error control schemes for near earth satellite communications
NASA Technical Reports Server (NTRS)
Lin, Shu; Kasami, Tadao
1986-01-01
Two hybrid automatic repeat request (ARQ) error control schemes are proposed for NASA near earth satellite communications. Both schemes are adaptive in nature, and employ cascaded codes to achieve both high reliability and throughput efficiency for high data rate file transfer.
Two hybrid ARQ error control schemes for near Earth satellite communications
NASA Technical Reports Server (NTRS)
Lin, S.
1986-01-01
Two hybrid Automatic Repeat Request (ARQ) error control schemes are proposed for NASA near Earth satellite communications. Both schemes are adaptive in nature, and employ cascaded codes to achieve both high reliability and throughput efficiency for high data rate file transfer.
Error control for reliable digital data transmission and storage systems
NASA Technical Reports Server (NTRS)
Costello, D. J., Jr.; Deng, R. H.
1985-01-01
A problem in designing semiconductor memories is to provide some measure of error control without requiring excessive coding overhead or decoding time. In LSI and VLSI technology, memories are often organized on a multiple bit (or byte) per chip basis. For example, some 256K-bit DRAM's are organized in 32Kx8 bit-bytes. Byte oriented codes such as Reed Solomon (RS) codes can provide efficient low overhead error control for such memories. However, the standard iterative algorithm for decoding RS codes is too slow for these applications. In this paper we present some special decoding techniques for extended single-and-double-error-correcting RS codes which are capable of high speed operation. These techniques are designed to find the error locations and the error values directly from the syndrome without having to use the iterative alorithm to find the error locator polynomial. Two codes are considered: (1) a d sub min = 4 single-byte-error-correcting (SBEC), double-byte-error-detecting (DBED) RS code; and (2) a d sub min = 6 double-byte-error-correcting (DBEC), triple-byte-error-detecting (TBED) RS code.
Statistical Physics for Adaptive Distributed Control
NASA Technical Reports Server (NTRS)
Wolpert, David H.
2005-01-01
A viewgraph presentation on statistical physics for distributed adaptive control is shown. The topics include: 1) The Golden Rule; 2) Advantages; 3) Roadmap; 4) What is Distributed Control? 5) Review of Information Theory; 6) Iterative Distributed Control; 7) Minimizing L(q) Via Gradient Descent; and 8) Adaptive Distributed Control.
Adaptive Control of Truss Structures for Gossamer Spacecraft
NASA Technical Reports Server (NTRS)
Yang Bong-Jun; Calise, anthony J.; Craig, James I.; Whorton, Mark S.
2007-01-01
Neural network-based adaptive control is considered for active control of a highly flexible truss structure which may be used to support solar sail membranes. The objective is to suppress unwanted vibrations in SAFE (Solar Array Flight Experiment) boom, a test-bed located at NASA. Compared to previous tests that restrained truss structures in planar motion, full three dimensional motions are tested. Experimental results illustrate the potential of adaptive control in compensating for nonlinear actuation and modeling error, and in rejecting external disturbances.
Flexible beam control using an adaptive truss
NASA Technical Reports Server (NTRS)
Warrington, Thomas J.; Horner, C. Garnett
1990-01-01
To demonstrate the feasibility of adaptive trusses for vibration suppression, a 12-ft-long beam is attached to a single cell of an adaptive truss which has three active battens. With the base of the adaptive truss attached to the laboratory frame, the measured strain of the vibrating beam shows the adaptive truss to be very effective in suppressing vibration when subjected to initial conditions. Control is accomplished by a PC/XT computer that implements an LQR-designed control law.
Flight Test Approach to Adaptive Control Research
NASA Technical Reports Server (NTRS)
Pavlock, Kate Maureen; Less, James L.; Larson, David Nils
2011-01-01
The National Aeronautics and Space Administration s Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The validation of adaptive controls has the potential to enhance safety in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.
Development of error criteria for adaptive multi-element polynomial chaos approaches
NASA Astrophysics Data System (ADS)
Chouvion, B.; Sarrouy, E.
2016-01-01
This paper presents and compares different methodologies to create an adaptive stochastic space partitioning in polynomial chaos applications which use a multi-element approach. To implement adaptive partitioning, Wan and Karniadakis first developed a criterion based on the relative error in local variance. We propose here two different error criteria: one based on the residual error and the other on the local variance discontinuity created by partitioning. The methods are applied to classical differential equations with long-term integration difficulties, including the Kraichnan-Orszag three-mode problem, and to simple linear and nonlinear mechanical systems whose stochastic dynamic responses are investigated. The efficiency and robustness of the approaches are investigated by comparison with Monte-Carlo simulations. For the different examples considered, they show significantly better convergence characteristics than the original error criterion used.
Adaptive, predictive controller for optimal process control
Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.
1995-12-01
One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network[2]. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns[3]. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.
Correctable noise of quantum-error-correcting codes under adaptive concatenation
NASA Astrophysics Data System (ADS)
Fern, Jesse
2008-01-01
We examine the transformation of noise under a quantum-error-correcting code (QECC) concatenated repeatedly with itself, by analyzing the effects of a quantum channel after each level of concatenation using recovery operators that are optimally adapted to use error syndrome information from the previous levels of the code. We use the Shannon entropy of these channels to estimate the thresholds of correctable noise for QECCs and find considerable improvements under this adaptive concatenation. Similar methods could be used to increase quantum-fault-tolerant thresholds.
Hybrid adaptive ascent flight control for a flexible launch vehicle
NASA Astrophysics Data System (ADS)
Lefevre, Brian D.
hybrid adaptive flight controller, development of a Newton's method based online parameter update that is modified to include a step size which regulates the rate of change in the parameter estimates, comparison of the modified Newton's method and recursive least squares online parameter update algorithms, modification of the neural network's input structure to accommodate for the nature of the nonlinearities present in a launch vehicle's ascent flight, examination of both tracking error based and modeling error based neural network weight update laws, and integration of feedback filters for the purpose of preventing harmful interaction between the flight control system and flexible structural modes. To validate the hybrid adaptive controller, a high-fidelity Ares I ascent flight simulator and a classical gain-scheduled proportional-integral-derivative (PID) ascent flight controller were obtained from the NASA Marshall Space Flight Center. The classical PID flight controller is used as a benchmark when analyzing the performance of the hybrid adaptive flight controller. Simulations are conducted which model both nominal and off-nominal flight conditions with structural flexibility of the vehicle either enabled or disabled. First, rigid body ascent simulations are performed with the hybrid adaptive controller under nominal flight conditions for the purpose of selecting the update laws which drive the indirect and direct adaptive components. With the neural network disabled, the results revealed that the recursive least squares online parameter update caused high frequency oscillations to appear in the engine gimbal commands. This is highly undesirable for long and slender launch vehicles, such as the Ares I, because such oscillation of the rocket nozzle could excite unstable structural flex modes. In contrast, the modified Newton's method online parameter update produced smooth control signals and was thus selected for use in the hybrid adaptive launch vehicle flight
Multilevel Error Estimation and Adaptive h-Refinement for Cartesian Meshes with Embedded Boundaries
NASA Technical Reports Server (NTRS)
Aftosmis, M. J.; Berger, M. J.; Kwak, Dochan (Technical Monitor)
2002-01-01
This paper presents the development of a mesh adaptation module for a multilevel Cartesian solver. While the module allows mesh refinement to be driven by a variety of different refinement parameters, a central feature in its design is the incorporation of a multilevel error estimator based upon direct estimates of the local truncation error using tau-extrapolation. This error indicator exploits the fact that in regions of uniform Cartesian mesh, the spatial operator is exactly the same on the fine and coarse grids, and local truncation error estimates can be constructed by evaluating the residual on the coarse grid of the restricted solution from the fine grid. A new strategy for adaptive h-refinement is also developed to prevent errors in smooth regions of the flow from being masked by shocks and other discontinuous features. For certain classes of error histograms, this strategy is optimal for achieving equidistribution of the refinement parameters on hierarchical meshes, and therefore ensures grid converged solutions will be achieved for appropriately chosen refinement parameters. The robustness and accuracy of the adaptation module is demonstrated using both simple model problems and complex three dimensional examples using meshes with from 10(exp 6), to 10(exp 7) cells.
Error estimation and adaptive order nodal method for solving multidimensional transport problems
Zamonsky, O.M.; Gho, C.J.; Azmy, Y.Y.
1998-01-01
The authors propose a modification of the Arbitrarily High Order Transport Nodal method whereby they solve each node and each direction using different expansion order. With this feature and a previously proposed a posteriori error estimator they develop an adaptive order scheme to automatically improve the accuracy of the solution of the transport equation. They implemented the modified nodal method, the error estimator and the adaptive order scheme into a discrete-ordinates code for solving monoenergetic, fixed source, isotropic scattering problems in two-dimensional Cartesian geometry. They solve two test problems with large homogeneous regions to test the adaptive order scheme. The results show that using the adaptive process the storage requirements are reduced while preserving the accuracy of the results.
Compton, Rebecca J; Hofheimer, Julia; Kazinka, Rebecca
2013-03-01
In this study, we tested the relationship between error-related signals of cognitive control and cortisol reactivity, investigating the hypothesis of common systems for cognitive and emotional self-regulation. Eighty-three participants completed a Stroop task while electroencephalography (EEG) was recorded. Three error-related indices were derived from the EEG: the error-related negativity (ERN), error positivity (Pe), and error-related alpha suppression (ERAS). Pre- and posttask salivary samples were assayed for cortisol, and cortisol change scores were correlated with the EEG variables. Better error-correct differentiation in the ERN predicted less cortisol increase during the task, whereas greater ERAS predicted greater cortisol increase during the task; the Pe was not correlated with cortisol changes. We concluded that an enhanced ERN, part of an adaptive cognitive control system, predicts successful stress regulation. In contrast, an enhanced ERAS response may reflect error-related arousal that is not adaptive. The results support the concept of overlapping systems for cognitive and emotional self-regulation. PMID:23055094
Adaptive and predictive control of a simulated robot arm.
Tolu, Silvia; Vanegas, Mauricio; Garrido, Jesús A; Luque, Niceto R; Ros, Eduardo
2013-06-01
In this work, a basic cerebellar neural layer and a machine learning engine are embedded in a recurrent loop which avoids dealing with the motor error or distal error problem. The presented approach learns the motor control based on available sensor error estimates (position, velocity, and acceleration) without explicitly knowing the motor errors. The paper focuses on how to decompose the input into different components in order to facilitate the learning process using an automatic incremental learning model (locally weighted projection regression (LWPR) algorithm). LWPR incrementally learns the forward model of the robot arm and provides the cerebellar module with optimal pre-processed signals. We present a recurrent adaptive control architecture in which an adaptive feedback (AF) controller guarantees a precise, compliant, and stable control during the manipulation of objects. Therefore, this approach efficiently integrates a bio-inspired module (cerebellar circuitry) with a machine learning component (LWPR). The cerebellar-LWPR synergy makes the robot adaptable to changing conditions. We evaluate how this scheme scales for robot-arms of a high number of degrees of freedom (DOFs) using a simulated model of a robot arm of the new generation of light weight robots (LWRs). PMID:23627657
Adaptive control of Hammerstein-Wiener nonlinear systems
NASA Astrophysics Data System (ADS)
Zhang, Bi; Hong, Hyokchan; Mao, Zhizhong
2016-07-01
The Hammerstein-Wiener model is a block-oriented model, having a linear dynamic block sandwiched by two static nonlinear blocks. This note develops an adaptive controller for a special form of Hammerstein-Wiener nonlinear systems which are parameterized by the key-term separation principle. The adaptive control law and recursive parameter estimation are updated by the use of internal variable estimations. By modeling the errors due to the estimation of internal variables, we establish convergence and stability properties. Theoretical results show that parameter estimation convergence and closed-loop system stability can be guaranteed under sufficient condition. From a qualitative analysis of the sufficient condition, we introduce an adaptive weighted factor to improve the performance of the adaptive controller. Numerical examples are given to confirm the results in this paper.
The effect of retinal image error update rate on human vestibulo-ocular reflex gain adaptation.
Fadaee, Shannon B; Migliaccio, Americo A
2016-04-01
The primary function of the angular vestibulo-ocular reflex (VOR) is to stabilise images on the retina during head movements. Retinal image movement is the likely feedback signal that drives VOR modification/adaptation for different viewing contexts. However, it is not clear whether a retinal image position or velocity error is used primarily as the feedback signal. Recent studies examining this signal are limited because they used near viewing to modify the VOR. However, it is not known whether near viewing drives VOR adaptation or is a pre-programmed contextual cue that modifies the VOR. Our study is based on analysis of the VOR evoked by horizontal head impulses during an established adaptation task. Fourteen human subjects underwent incremental unilateral VOR adaptation training and were tested using the scleral search coil technique over three separate sessions. The update rate of the laser target position (source of the retinal image error signal) used to drive VOR adaptation was different for each session [50 (once every 20 ms), 20 and 15/35 Hz]. Our results show unilateral VOR adaptation occurred at 50 and 20 Hz for both the active (23.0 ± 9.6 and 11.9 ± 9.1% increase on adapting side, respectively) and passive VOR (13.5 ± 14.9, 10.4 ± 12.2%). At 15 Hz, unilateral adaptation no longer occurred in the subject group for both the active and passive VOR, whereas individually, 4/9 subjects tested at 15 Hz had significant adaptation. Our findings suggest that 1-2 retinal image position error signals every 100 ms (i.e. target position update rate 15-20 Hz) are sufficient to drive VOR adaptation. PMID:26715411
Hussain, Sara J; Hanson, Angela S; Tseng, Shih-Chiao; Morton, Susanne M
2013-08-01
Locomotor patterns are generally very consistent but also contain a high degree of adaptability. Motor adaptation is a short-term type of learning that utilizes this plasticity to alter locomotor behaviors quickly and transiently. In this study, we used a variation of an adaptation paradigm in order to test whether explicit information as well as the removal of the visual error signal after adaptation could improve retention of a newly learned walking pattern 24 h later. On two consecutive days of testing, participants walked on a treadmill while viewing a visual display that showed erroneous feedback of swing times for each leg. Participants were instructed to use this feedback to monitor and adjust swing times so they appeared symmetric within the display. This was achieved by producing a novel interlimb asymmetry between legs. For both legs, we measured adaptation magnitudes and rates and immediate and 24-h retention magnitudes. Participants showed similar adaptation on both days but a faster rate of readaptation on day 2. There was complete retention of adapted swing times on the increasing leg (i.e., no evidence of performance decay over 24 h). Overall, these findings suggest that the inclusion of explicit information and the removal of the visual error signal are effective in inducing full retention of adapted increases in swing time over a moderate (24 h) interval of time. PMID:23741038
Research in digital adaptive flight controllers
NASA Technical Reports Server (NTRS)
Kaufman, H.
1976-01-01
A design study of adaptive control logic suitable for implementation in modern airborne digital flight computers was conducted. Both explicit controllers which directly utilize parameter identification and implicit controllers which do not require identification were considered. Extensive analytical and simulation efforts resulted in the recommendation of two explicit digital adaptive flight controllers. Interface weighted least squares estimation procedures with control logic were developed using either optimal regulator theory or with control logic based upon single stage performance indices.
Error-measure for anisotropic grid-adaptation in turbulence-resolving simulations
NASA Astrophysics Data System (ADS)
Toosi, Siavash; Larsson, Johan
2015-11-01
Grid-adaptation requires an error-measure that identifies where the grid should be refined. In the case of turbulence-resolving simulations (DES, LES, DNS), a simple error-measure is the small-scale resolved energy, which scales with both the modeled subgrid-stresses and the numerical truncation errors in many situations. Since this is a scalar measure, it does not carry any information on the anisotropy of the optimal grid-refinement. The purpose of this work is to introduce a new error-measure for turbulence-resolving simulations that is capable of predicting nearly-optimal anisotropic grids. Turbulent channel flow at Reτ ~ 300 is used to assess the performance of the proposed error-measure. The formulation is geometrically general, applicable to any type of unstructured grid.
Survey of adaptive control using Liapunov design
NASA Technical Reports Server (NTRS)
Lindorff, D. P.; Carroll, R. L.
1973-01-01
A survey of the literature in which Liapunov's second method is used in determining the control law is presented, with emphasis placed on the model-tracking adaptive control problem. Forty references are listed. Following a brief tutorial exposition of the adaptive control problem, the techniques for treating reduction of order, disturbance and time-varying parameters, multivariable systems, identification, and adaptive observers are discussed. The method is critically evaluated, particularly with respect to possibilities for application.
An adaptive Cartesian control scheme for manipulators
NASA Technical Reports Server (NTRS)
Seraji, H.
1987-01-01
A adaptive control scheme for direct control of manipulator end-effectors to achieve trajectory tracking in Cartesian space is developed. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for online implementation with high sampling rates.
Composite Gauss-Legendre Quadrature with Error Control
ERIC Educational Resources Information Center
Prentice, J. S. C.
2011-01-01
We describe composite Gauss-Legendre quadrature for determining definite integrals, including a means of controlling the approximation error. We compare the form and performance of the algorithm with standard Newton-Cotes quadrature. (Contains 1 table.)
High Dimensional Variable Selection with Error Control.
Kim, Sangjin; Halabi, Susan
2016-01-01
Background. The iterative sure independence screening (ISIS) is a popular method in selecting important variables while maintaining most of the informative variables relevant to the outcome in high throughput data. However, it not only is computationally intensive but also may cause high false discovery rate (FDR). We propose to use the FDR as a screening method to reduce the high dimension to a lower dimension as well as controlling the FDR with three popular variable selection methods: LASSO, SCAD, and MCP. Method. The three methods with the proposed screenings were applied to prostate cancer data with presence of metastasis as the outcome. Results. Simulations showed that the three variable selection methods with the proposed screenings controlled the predefined FDR and produced high area under the receiver operating characteristic curve (AUROC) scores. In applying these methods to the prostate cancer example, LASSO and MCP selected 12 and 8 genes and produced AUROC scores of 0.746 and 0.764, respectively. Conclusions. We demonstrated that the variable selection methods with the sequential use of FDR and ISIS not only controlled the predefined FDR in the final models but also had relatively high AUROC scores. PMID:27597974
High Dimensional Variable Selection with Error Control
2016-01-01
Background. The iterative sure independence screening (ISIS) is a popular method in selecting important variables while maintaining most of the informative variables relevant to the outcome in high throughput data. However, it not only is computationally intensive but also may cause high false discovery rate (FDR). We propose to use the FDR as a screening method to reduce the high dimension to a lower dimension as well as controlling the FDR with three popular variable selection methods: LASSO, SCAD, and MCP. Method. The three methods with the proposed screenings were applied to prostate cancer data with presence of metastasis as the outcome. Results. Simulations showed that the three variable selection methods with the proposed screenings controlled the predefined FDR and produced high area under the receiver operating characteristic curve (AUROC) scores. In applying these methods to the prostate cancer example, LASSO and MCP selected 12 and 8 genes and produced AUROC scores of 0.746 and 0.764, respectively. Conclusions. We demonstrated that the variable selection methods with the sequential use of FDR and ISIS not only controlled the predefined FDR in the final models but also had relatively high AUROC scores. PMID:27597974
Ishikawa, Takumi; Sakaguchi, Yutaka
2013-01-01
An important issue in motor learning/adaptation research is how the brain accepts the error information necessary for maintaining and improving task performance in a changing environment. The present study focuses on the effect of timing of error feedback. Previous research has demonstrated that adaptation to displacement of the visual field by prisms in a manual reaching task is significantly slowed by delayed visual feedback of the endpoint, suggesting that error feedback is most effective when given at the end of a movement. To further elucidate the brain mechanism by which error information is accepted in visuomotor adaptation, we tested whether error acceptance is linked to the end of a given task or to the end of an executed movement. We conducted a behavioral experiment using a virtual shooting task in which subjects controlled their wrist movements to meet a target with a cursor as accurately as possible. We manipulated the timing of visual feedback of the impact position so that it occurred either ahead of or behind the true time of impact. In another condition, the impact timing was explicitly indicated by an additional cue. The magnitude of the aftereffect significantly varied depending on the timing of feedback (p < 0.05, Friedman's Test). Interestingly, two distinct peaks of aftereffect were observed around movement-end and around task-end, irrespective of the existence of the timing cue. However, the peak around task-end was sharper when the timing cue was given. Our results demonstrate that the brain efficiently accepts error information at both movement-end and task-end, suggesting that two different learning mechanisms may underlie visuomotor transformation. PMID:23393602
Adaptive control of dual-arm robots
NASA Technical Reports Server (NTRS)
Seraji, H.
1987-01-01
Three strategies for adaptive control of cooperative dual-arm robots are described. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through the load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions, while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are rejected by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. The controllers have simple structures and are computationally fast for on-line implementation with high sampling rates.
p-adaption for compressible flow problems using a goal-based error estimator
NASA Astrophysics Data System (ADS)
Ekelschot, Dirk; Moxey, David; Peiro, Joaquim; Sherwin, Spencer
2014-11-01
We present an approach of applying p-adaption to compressible flow problems using a dual-weighted error estimator. This technique has been implemented in the high-order h/p spectral element library Nektar + + . The compressible solver uses a high-order discontinuous Galerkin (DG) discretization. This approach is generally considered to be expensive and that is why the introduced p-adaption technique aims for lowering the computational cost while preserving the high-order accuracy and the exponential convergence properties. The numerical fluxes between the elements are discontinuous which allows one to use a different polynomial order in each element. After identifying and localizing the sources of error, the order of approximation of the solution within the element is improved. The solution to the adjoint equations for the compressible Euler equations is used to weigh the local residual of the primal solution. This provides both the error in the target quantity, which is typically the lift or drag coefficient, and an indication on how sensitive the local solution is to the target quantity. The dual-weighted error within each element serves then as a local refinement indicator that drives the p-adaptive algorithm. The performance of this p-adaptive method is demonstrated using a test case of subsonic flow past a 3D wing geometry.
The Influence of Item Calibration Error on Variable-Length Computerized Adaptive Testing
ERIC Educational Resources Information Center
Patton, Jeffrey M.; Cheng, Ying; Yuan, Ke-Hai; Diao, Qi
2013-01-01
Variable-length computerized adaptive testing (VL-CAT) allows both items and test length to be "tailored" to examinees, thereby achieving the measurement goal (e.g., scoring precision or classification) with as few items as possible. Several popular test termination rules depend on the standard error of the ability estimate, which in turn depends…
Verifiable Adaptive Control with Analytical Stability Margins by Optimal Control Modification
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2010-01-01
This paper presents a verifiable model-reference adaptive control method based on an optimal control formulation for linear uncertain systems. A predictor model is formulated to enable a parameter estimation of the system parametric uncertainty. The adaptation is based on both the tracking error and predictor error. Using a singular perturbation argument, it can be shown that the closed-loop system tends to a linear time invariant model asymptotically under an assumption of fast adaptation. A stability margin analysis is given to estimate a lower bound of the time delay margin using a matrix measure method. Using this analytical method, the free design parameter n of the optimal control modification adaptive law can be determined to meet a specification of stability margin for verification purposes.
Automatic Time Stepping with Global Error Control for Groundwater Flow Models
Tang, Guoping
2008-09-01
An automatic time stepping with global error control is proposed for the time integration of the diffusion equation to simulate groundwater flow in confined aquifers. The scheme is based on an a posteriori error estimate for the discontinuous Galerkin (dG) finite element methods. A stability factor is involved in the error estimate and it is used to adapt the time step and control the global temporal error for the backward difference method. The stability factor can be estimated by solving a dual problem. The stability factor is not sensitive to the accuracy of the dual solution and the overhead computational cost can be minimized by solving the dual problem using large time steps. Numerical experiments are conducted to show the application and the performance of the automatic time stepping scheme. Implementation of the scheme can lead to improvement in accuracy and efficiency for groundwater flow models.
Adaptive neural network motion control of manipulators with experimental evaluations.
Puga-Guzmán, S; Moreno-Valenzuela, J; Santibáñez, V
2014-01-01
A nonlinear proportional-derivative controller plus adaptive neuronal network compensation is proposed. With the aim of estimating the desired torque, a two-layer neural network is used. Then, adaptation laws for the neural network weights are derived. Asymptotic convergence of the position and velocity tracking errors is proven, while the neural network weights are shown to be uniformly bounded. The proposed scheme has been experimentally validated in real time. These experimental evaluations were carried in two different mechanical systems: a horizontal two degrees-of-freedom robot and a vertical one degree-of-freedom arm which is affected by the gravitational force. In each one of the two experimental set-ups, the proposed scheme was implemented without and with adaptive neural network compensation. Experimental results confirmed the tracking accuracy of the proposed adaptive neural network-based controller. PMID:24574910
Error control coding for multi-frequency modulation
NASA Astrophysics Data System (ADS)
Ives, Robert W.
1990-06-01
Multi-frequency modulation (MFM) has been developed at NPS using both quadrature-phase-shift-keyed (QPSK) and quadrature-amplitude-modulated (QAM) signals with good bit error performance at reasonable signal-to-noise ratios. Improved performance can be achieved by the introduction of error control coding. This report documents a FORTRAN simulation of the implementation of error control coding into an MFM communication link with additive white Gaussian noise. Four Reed-Solomon codes were incorporated, two for 16-QAM and two for 32-QAM modulation schemes. The error control codes used were modified from the conventional Reed-Solomon codes in that one information symbol was sacrificed to parity in order to use a simplified decoding algorithm which requires no iteration and enhances error detection capability. Bit error rates as a function of SNR and E(sub b)/N(sub 0) were analyzed, and bit error performance was weighed against reduction in information rate to determine the value of the codes.
On Using Exponential Parameter Estimators with an Adaptive Controller
NASA Technical Reports Server (NTRS)
Patre, Parag; Joshi, Suresh M.
2011-01-01
Typical adaptive controllers are restricted to using a specific update law to generate parameter estimates. This paper investigates the possibility of using any exponential parameter estimator with an adaptive controller such that the system tracks a desired trajectory. The goal is to provide flexibility in choosing any update law suitable for a given application. The development relies on a previously developed concept of controller/update law modularity in the adaptive control literature, and the use of a converse Lyapunov-like theorem. Stability analysis is presented to derive gain conditions under which this is possible, and inferences are made about the tracking error performance. The development is based on a class of Euler-Lagrange systems that are used to model various engineering systems including space robots and manipulators.
QOS-aware error recovery in wireless body sensor networks using adaptive network coding.
Razzaque, Mohammad Abdur; Javadi, Saeideh S; Coulibaly, Yahaya; Hira, Muta Tah
2015-01-01
Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts. PMID:25551485
QoS-Aware Error Recovery in Wireless Body Sensor Networks Using Adaptive Network Coding
Razzaque, Mohammad Abdur; Javadi, Saeideh S.; Coulibaly, Yahaya; Hira, Muta Tah
2015-01-01
Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts. PMID:25551485
Hofheimer, Julia; Kazinka, Rebecca
2012-01-01
In this study, we tested the relationship between error-related signals of cognitive control and cortisol reactivity, investigating the hypothesis of common systems for cognitive and emotional self-regulation. Eighty-three participants completed a Stroop task while electroencephalography (EEG) was recorded. Three error-related indices were derived from the EEG: the error-related negativity (ERN), error positivity (Pe), and error-related alpha suppression (ERAS). Pre- and posttask salivary samples were assayed for cortisol, and cortisol change scores were correlated with the EEG variables. Better error–correct differentiation in the ERN predicted less cortisol increase during the task, whereas greater ERAS predicted greater cortisol increase during the task; the Pe was not correlated with cortisol changes. We concluded that an enhanced ERN, part of an adaptive cognitive control system, predicts successful stress regulation. In contrast, an enhanced ERAS response may reflect error-related arousal that is not adaptive. The results support the concept of overlapping systems for cognitive and emotional self-regulation. PMID:23055094
Adaptive control in the presence of unmodeled dynamics. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Rohrs, C. E.
1982-01-01
Stability and robustness properties of a wide class of adaptive control algorithms in the presence of unmodeled dynamics and output disturbances were investigated. The class of adaptive algorithms considered are those commonly referred to as model reference adaptive control algorithms, self-tuning controllers, and dead beat adaptive controllers, developed for both continuous-time systems and discrete-time systems. A unified analytical approach was developed to examine the class of existing adaptive algorithms. It was discovered that all existing algorithms contain an infinite gain operator in the dynamic system that defines command reference errors and parameter errors; it is argued that such an infinite gain operator appears to be generic to all adaptive algorithms, whether they exhibit explicit or implicit parameter identification. It is concluded that none of the adaptive algorithms considered can be used with confidence in a practical control system design, because instability will set in with a high probability.
NASA Astrophysics Data System (ADS)
Lee, J.; Yoon, M.; Lee, J.
2014-12-01
Current Global Navigation Satellite Systems (GNSS) augmentation systems attempt to consider all possible ionospheric events in their correction computations of worst-case errors. This conservatism can be mitigated by subdividing anomalous conditions and using different values of ionospheric threat-model bounds for each class. A new concept of 'real-time ionospheric threat adaptation' that adjusts the threat model in real time instead of always using the same 'worst-case' model was introduced in my previous research. The concept utilizes predicted values of space weather indices for determining the corresponding threat model based on the pre-defined worst-case threat as a function of space weather indices. Since space weather prediction is not reliable due to prediction errors, prediction errors are needed to be bounded to the required level of integrity of the system being supported. The previous research performed prediction error bounding using disturbance, storm time (Dst) index. The distribution of Dst prediction error over the 15-year data was bounded by applying 'inflated-probability density function (pdf) Gaussian bounding'. Since the error distribution has thick and non-Gaussian tails, investigation on statistical distributions which properly describe heavy tails with less conservatism is required for the system performance. This paper suggests two potential approaches for improving space weather prediction error bounding. First, we suggest using different statistical models when fit the error distribution, such as the Laplacian distribution which has fat tails, and the folded Gaussian cumulative distribution function (cdf) distribution. Second approach is to bound the error distribution by segregating data based on the overall level of solar activity. Bounding errors using only solar minimum period data will have less uncertainty and it may allow the use of 'solar cycle prediction' provided by NASA when implementing to real-time threat adaptation. Lastly
Dynamic optimization and adaptive controller design
NASA Astrophysics Data System (ADS)
Inamdar, S. R.
2010-10-01
In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.
Dynamically corrected gates for singlet-triplet spin qubits with control-dependent errors
NASA Astrophysics Data System (ADS)
Jacobson, N. Tobias; Witzel, Wayne M.; Nielsen, Erik; Carroll, Malcolm S.
2013-03-01
Magnetic field inhomogeneity due to random polarization of quasi-static local magnetic impurities is a major source of environmentally induced error for singlet-triplet double quantum dot (DQD) spin qubits. Moreover, for singlet-triplet qubits this error may depend on the applied controls. This effect is significant when a static magnetic field gradient is applied to enable full qubit control. Through a configuration interaction analysis, we observe that the dependence of the field inhomogeneity-induced error on the DQD bias voltage can vary systematically as a function of the controls for certain experimentally relevant operating regimes. To account for this effect, we have developed a straightforward prescription for adapting dynamically corrected gate sequences that assume control-independent errors into sequences that compensate for systematic control-dependent errors. We show that accounting for such errors may lead to a substantial increase in gate fidelities. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. DOE's National Nuclear Security Administration under contract DE-AC04-94AL85000.
Research on error control and compensation in magnetorheological finishing.
Dai, Yifan; Hu, Hao; Peng, Xiaoqiang; Wang, Jianmin; Shi, Feng
2011-07-01
Although magnetorheological finishing (MRF) is a deterministic finishing technology, the machining results always fall short of simulation precision in the actual process, and it cannot meet the precision requirements just through a single treatment but after several iterations. We investigate the reasons for this problem through simulations and experiments. Through controlling and compensating the chief errors in the manufacturing procedure, such as removal function calculation error, positioning error of the removal function, and dynamic performance limitation of the CNC machine, the residual error convergence ratio (ratio of figure error before and after processing) in a single process is obviously increased, and higher figure precision is achieved. Finally, an improved technical process is presented based on these researches, and the verification experiment is accomplished on the experimental device we developed. The part is a circular plane mirror of fused silica material, and the surface figure error is improved from the initial λ/5 [peak-to-valley (PV) λ=632.8 nm], λ/30 [root-mean-square (rms)] to the final λ/40 (PV), λ/330 (rms) just through one iteration in 4.4 min. Results show that a higher convergence ratio and processing precision can be obtained by adopting error control and compensation techniques in MRF. PMID:21743536
Ham, Timothy; Leff, Alex; de Boissezon, Xavier; Joffe, Anna; Sharp, David J
2013-04-17
The Salience Network (SN) consists of the dorsal anterior cingulate cortex (dACC) and bilateral insulae. The network responds to behaviorally salient events, and an important question is how its nodes interact. One theory is that the dACC provides the earliest cortical signal of behaviorally salient events, such as errors. Alternatively, the anterior right insula (aRI) has been proposed to provide an early cognitive control signal. As these regions frequently coactivate, it has been difficult to disentangle their roles using conventional methods. Here we use dynamic causal modeling and a Bayesian model evidence technique to investigate the causal relationships between nodes in the SN after errors. Thirty-five human subjects performed the Simon task. The task has two conditions (congruent and incongruent) producing two distinct error types. Neural activity associated with errors was investigated using fMRI. Subjects made a total of 1319 congruent and 1617 incongruent errors. Errors resulted in robust activation of the SN. Dynamic causal modeling analyses demonstrated that input into the SN was most likely via the aRI for both error types and that the aRI was the only region intrinsically connected to both other nodes. Only incongruent errors produced behavioral adaptation, and the strength of the connection between the dACC and the left insulae correlated with the extent of this behavioral change. We conclude that the aRI, not the dACC, drives the SN after errors on an attentionally demanding task, and that a change in the effective connectivity of the dACC is associated with behavioral adaptation after errors. PMID:23595766
When soft controls get slippery: User interfaces and human error
Stubler, W.F.; O`Hara, J.M.
1998-12-01
Many types of products and systems that have traditionally featured physical control devices are now being designed with soft controls--input formats appearing on computer-based display devices and operated by a variety of input devices. A review of complex human-machine systems found that soft controls are particularly prone to some types of errors and may affect overall system performance and safety. This paper discusses the application of design approaches for reducing the likelihood of these errors and for enhancing usability, user satisfaction, and system performance and safety.
On the undetected error probability of a concatenated coding scheme for error control
NASA Technical Reports Server (NTRS)
Deng, H.; Costello, D. J., Jr.
1984-01-01
Consider a concatenated coding scheme for error control on a binary symmetric channel, called the inner channel. The bit error rate (BER) of the channel is correspondingly called the inner BER, and is denoted by Epsilon (sub i). Two linear block codes, C(sub f) and C(sub b), are used. The inner code C(sub f), called the frame code, is an (n,k) systematic binary block code with minimum distance, d(sub f). The frame code is designed to correct + or fewer errors and simultaneously detect gamma (gamma +) or fewer errors, where + + gamma + 1 = to or d(sub f). The outer code C(sub b) is either an (n(sub b), K(sub b)) binary block with a n(sub b) = mk, or an (n(sub b), k(Sub b) maximum distance separable (MDS) code with symbols from GF(q), where q = 2(b) and the code length n(sub b) satisfies n(sub)(b) = mk. The integerim is the number of frames. The outercode is designed for error detection only.
Adaptive control applied to Space Station attitude control system
NASA Technical Reports Server (NTRS)
Lam, Quang M.; Chipman, Richard; Hu, Tsay-Hsin G.; Holmes, Eric B.; Sunkel, John
1992-01-01
This paper presents an adaptive control approach to enhance the performance of current attitude control system used by the Space Station Freedom. The proposed control law was developed based on the direct adaptive control or model reference adaptive control scheme. Performance comparisons, subject to inertia variation, of the adaptive controller and the fixed-gain linear quadratic regulator currently implemented for the Space Station are conducted. Both the fixed-gain and the adaptive gain controllers are able to maintain the Station stability for inertia variations of up to 35 percent. However, when a 50 percent inertia variation is applied to the Station, only the adaptive controller is able to maintain the Station attitude.
Experimental implementation of adaptive control for flexible space structures
NASA Technical Reports Server (NTRS)
Mcgraw, Gary A.
1988-01-01
On-going research at The Aerospace Corporation studying the feasibility of applying adaptive control methodologies to the control of flexible space structures is described. A laboratory testbed was established to test system identification and control approaches. The laboratory set-up and controller design approach are discussed. The ARX least squares parameter estimation technique is analyzed in terms of frequency domain transfer function bias error. This analysis approach enables the determination of the effects of sampling rate, sensor type, and data prefiltering on the estimation performance. The ability to identify space structure dynamics over a range of frequencies is shown to be heavily dependent on these factors.
Flight Approach to Adaptive Control Research
NASA Technical Reports Server (NTRS)
Pavlock, Kate Maureen; Less, James L.; Larson, David Nils
2011-01-01
The National Aeronautics and Space Administration's Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The testbed served as a full-scale vehicle to test and validate adaptive flight control research addressing technical challenges involved with reducing risk to enable safe flight in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.
Adaptive muffler based on controlled flow valves.
Šteblaj, Peter; Čudina, Mirko; Lipar, Primož; Prezelj, Jurij
2015-06-01
An adaptive muffler with a flexible internal structure is considered. Flexibility is achieved using controlled flow valves. The proposed adaptive muffler is able to adapt to changes in engine operating conditions. It consists of a Helmholtz resonator, expansion chamber, and quarter wavelength resonator. Different combinations of the control valves' states at different operating conditions define the main working principle. To control the valve's position, an active noise control approach was used. With the proposed muffler, the transmission loss can be increased by more than 10 dB in the selected frequency range. PMID:26093462
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Ishihara, Abraham; Stepanyan, Vahram; Boskovic, Jovan
2009-01-01
Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. The model matching conditions in the transformed time coordinate results in increase in the feedback gain and modification of the adaptive law.
Adaptive Impedance Control Of Redundant Manipulators
NASA Technical Reports Server (NTRS)
Seraji, Homayoun; Colbaugh, Richard D.; Glass, Kristin L.
1994-01-01
Improved method of controlling mechanical impedance of end effector of redundant robotic manipulator based on adaptive-control theory. Consists of two subsystems: adaptive impedance controller generating force-control inputs in Cartesian space of end effector to provide desired end-effector-impedance characteristics, and subsystem implementing algorithm that maps force-control inputs into torques applied to joints of manipulator. Accurate control of end effector and effective utilization of redundancy achieved simultaneously by use of method. Potential use to improve performance of such typical impedance-control tasks as deburring edges and accommodating transitions between unconstrained and constrained motions of end effectors.
Servo control booster system for minimizing following error
Wise, W.L.
1979-07-26
A closed-loop feedback-controlled servo system is disclosed which reduces command-to-response error to the system's position feedback resolution least increment, ..delta..S/sub R/, on a continuous real-time basis, for all operational times of consequence and for all operating speeds. The servo system employs a second position feedback control loop on a by exception basis, when the command-to-response error greater than or equal to ..delta..S/sub R/, to produce precise position correction signals. When the command-to-response error is less than ..delta..S/sub R/, control automatically reverts to conventional control means as the second position feedback control loop is disconnected, becoming transparent to conventional servo control means. By operating the second unique position feedback control loop used herein at the appropriate clocking rate, command-to-response error may be reduced to the position feedback resolution least increment. The present system may be utilized in combination with a tachometer loop for increased stability.
Adaptive spacecraft attitude control utilizing eigenaxis rotations
NASA Technical Reports Server (NTRS)
Cochran, J. E., Jr.; Colburn, B. K.; Speakman, N. O.
1975-01-01
Conventional and adaptive attitude control of spacecraft which use control moment gyros (CMG's) as torque sources are discussed. Control laws predicated on the assumption of a linear system are used since the spacecraft equations of motion are formulated in an 'eigenaxis system' so that they are essentially linear during 'slow' maneuvers even if large angles are involved. The overall control schemes are 'optimal' in several senses. Eigenaxis rotations and a weighted pseudo-inverse CMG steering law are used and, in the adaptive case, a Model Reference Adaptive System (MRAS) controller based on Liapunov's Second Method is adopted. To substantiate the theory, digital simulation results obtained using physical parameters of a Large Space Telescope type spacecraft are presented. These results indicate that an adaptive control law is often desirable.
Digital adaptive control laws for VTOL aircraft
NASA Technical Reports Server (NTRS)
Hartmann, G. L.; Stein, G.
1979-01-01
Honeywell has designed a digital self-adaptive flight control system for flight test in the VALT Research Aircraft (a modified CH-47). The final design resulted from a comparison of two different adaptive concepts: one based on explicit parameter estimates from a real-time maximum likelihood estimation algorithm and the other based on an implicit model reference adaptive system. The two designs are compared on the basis of performance and complexity.
The adaptive control system of acetylene generator
NASA Astrophysics Data System (ADS)
Kovaliuk, D. O.; Kovaliuk, Oleg; Burlibay, Aron; Gromaszek, Konrad
2015-12-01
The method of acetylene production in acetylene generator was analyzed. It was found that impossible to provide the desired process characteristics by the PID-controller. The adaptive control system of acetylene generator was developed. The proposed system combines the classic controller and fuzzy subsystem for controller parameters tuning.
Optimal control of quaternion propagation errors in spacecraft navigation
NASA Technical Reports Server (NTRS)
Vathsal, S.
1986-01-01
Optimal control techniques are used to drive the numerical error (truncation, roundoff, commutation) in computing the quaternion vector to zero. The normalization of the quaternion is carried out by appropriate choice of a performance index, which can be optimized. The error equations are derived from Friedland's (1978) theoretical development, and a matrix Riccati equation results for the computation of the gain matrix. Simulation results show that a high precision of the order of 10 to the -12th can be obtained using this technique in meeting the q(T)q=1 constraint. The performance of the estimator in the presence of the feedback control that maintains the normalization, is studied.
Reliability, Safety and Error Recovery for Advanced Control Software
NASA Technical Reports Server (NTRS)
Malin, Jane T.
2003-01-01
For long-duration automated operation of regenerative life support systems in space environments, there is a need for advanced integration and control systems that are significantly more reliable and safe, and that support error recovery and minimization of operational failures. This presentation outlines some challenges of hazardous space environments and complex system interactions that can lead to system accidents. It discusses approaches to hazard analysis and error recovery for control software and challenges of supporting effective intervention by safety software and the crew.
Li, Lebao; Sun, Lingling; Zhang, Shengzhou
2016-05-01
A new mean deviation coupling synchronization control strategy is developed for multiple motor control systems, which can guarantee the synchronization performance of multiple motor control systems and reduce complexity of the control structure with the increasing number of motors. The mean deviation coupling synchronization control architecture combining second-order adaptive sliding mode control (SOASMC) approach is proposed, which can improve synchronization control precision of multiple motor control systems and make speed tracking errors, mean speed errors of each motor and speed synchronization errors converge to zero rapidly. The proposed control scheme is robustness to parameter variations and random external disturbances and can alleviate the chattering phenomena. Moreover, an adaptive law is employed to estimate the unknown bound of uncertainty, which is obtained in the sense of Lyapunov stability theorem to minimize the control effort. Performance comparisons with master-slave control, relative coupling control, ring coupling control, conventional PI control and SMC are investigated on a four-motor synchronization control system. Extensive comparative results are given to shown the good performance of the proposed control scheme. PMID:26899554
Adaptive Flight Control Research at NASA
NASA Technical Reports Server (NTRS)
Motter, Mark A.
2008-01-01
A broad overview of current adaptive flight control research efforts at NASA is presented, as well as some more detailed discussion of selected specific approaches. The stated objective of the Integrated Resilient Aircraft Control Project, one of NASA s Aviation Safety programs, is to advance the state-of-the-art of adaptive controls as a design option to provide enhanced stability and maneuverability margins for safe landing in the presence of adverse conditions such as actuator or sensor failures. Under this project, a number of adaptive control approaches are being pursued, including neural networks and multiple models. Validation of all the adaptive control approaches will use not only traditional methods such as simulation, wind tunnel testing and manned flight tests, but will be augmented with recently developed capabilities in unmanned flight testing.
Implementation of a mesh adaptive scheme based on an element-level error indicator
NASA Technical Reports Server (NTRS)
Keating, Scott; Felippa, Carlos A.; Militello, Carmelo
1993-01-01
We investigate the formulation and application of element-level error indicators based on parametrized variational principles. The qualifier 'element-level' means that no information from adjacent elements is used for error estimation. This property is ideally suited to drive adaptive mesh refinement on parallel computers where access to neighboring elements resident on different processors may incur significant computational overhead. Furthermore, such indicators are not affected by physical jumps at junctures or interfaces. An element-level indicator has been derived from the higher-order element energy and applied to r and h mesh adaptation of meshes in plates and shell structures. We report on our initial experiments with a cylindrical shell that intersects with fist plates forming a simplified 'wing-body intersection' benchmark problem.
Wang, Shun-Yuan; Tseng, Chwan-Lu; Lin, Shou-Chuang; Chiu, Chun-Jung; Chou, Jen-Hsiang
2015-01-01
This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC) in the speed sensorless vector control of an induction motor (IM) drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes—the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC—were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE) was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes. PMID:25815450
NASA Astrophysics Data System (ADS)
Shi, Lei; Wang, Z. J.
2015-08-01
Adjoint-based mesh adaptive methods are capable of distributing computational resources to areas which are important for predicting an engineering output. In this paper, we develop an adjoint-based h-adaptation approach based on the high-order correction procedure via reconstruction formulation (CPR) to minimize the output or functional error. A dual-consistent CPR formulation of hyperbolic conservation laws is developed and its dual consistency is analyzed. Super-convergent functional and error estimate for the output with the CPR method are obtained. Factors affecting the dual consistency, such as the solution point distribution, correction functions, boundary conditions and the discretization approach for the non-linear flux divergence term, are studied. The presented method is then used to perform simulations for the 2D Euler and Navier-Stokes equations with mesh adaptation driven by the adjoint-based error estimate. Several numerical examples demonstrate the ability of the presented method to dramatically reduce the computational cost comparing with uniform grid refinement.
Decentralized digital adaptive control of robot motion
NASA Technical Reports Server (NTRS)
Tarokh, M.
1990-01-01
A decentralized model reference adaptive scheme is developed for digital control of robot manipulators. The adaptation laws are derived using hyperstability theory, which guarantees asymptotic trajectory tracking despite gross robot parameter variations. The control scheme has a decentralized structure in the sense that each local controller receives only its joint angle measurement to produce its joint torque. The independent joint controllers have simple structures and can be programmed using a very simple and computationally fast algorithm. As a result, the scheme is suitable for real-time motion control.
Self-Tuning Adaptive-Controller Using Online Frequency Identification
NASA Technical Reports Server (NTRS)
Chiang, W. W.; Cannon, R. H., Jr.
1985-01-01
A real time adaptive controller was designed and tested successfully on a fourth order laboratory dynamic system which features very low structural damping and a noncolocated actuator sensor pair. The controller, implemented in a digital minicomputer, consists of a state estimator, a set of state feedback gains, and a frequency locked loop (FLL) for real time parameter identification. The FLL can detect the closed loop natural frequency of the system being controlled, calculate the mismatch between a plant parameter and its counterpart in the state estimator, and correct the estimator parameter in real time. The adaptation algorithm can correct the controller error and stabilize the system for more than 50% variation in the plant natural frequency, compared with a 10% stability margin in frequency variation for a fixed gain controller having the same performance at the nominal plant condition. After it has locked to the correct plant frequency, the adaptive controller works as well as the fixed gain controller does when there is no parameter mismatch. The very rapid convergence of this adaptive system is demonstrated experimentally, and can also be proven with simple root locus methods.
Artificial neural network implementation of a near-ideal error prediction controller
NASA Technical Reports Server (NTRS)
Mcvey, Eugene S.; Taylor, Lynore Denise
1992-01-01
A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error
Optimal Control Modification Adaptive Law for Time-Scale Separated Systems
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2010-01-01
Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.
On Fractional Model Reference Adaptive Control
Shi, Bao; Dong, Chao
2014-01-01
This paper extends the conventional Model Reference Adaptive Control systems to fractional ones based on the theory of fractional calculus. A control law and an incommensurate fractional adaptation law are designed for the fractional plant and the fractional reference model. The stability and tracking convergence are analyzed using the frequency distributed fractional integrator model and Lyapunov theory. Moreover, numerical simulations of both linear and nonlinear systems are performed to exhibit the viability and effectiveness of the proposed methodology. PMID:24574897
On fractional Model Reference Adaptive Control.
Shi, Bao; Yuan, Jian; Dong, Chao
2014-01-01
This paper extends the conventional Model Reference Adaptive Control systems to fractional ones based on the theory of fractional calculus. A control law and an incommensurate fractional adaptation law are designed for the fractional plant and the fractional reference model. The stability and tracking convergence are analyzed using the frequency distributed fractional integrator model and Lyapunov theory. Moreover, numerical simulations of both linear and nonlinear systems are performed to exhibit the viability and effectiveness of the proposed methodology. PMID:24574897
Simple adaptive tracking control for mobile robots
NASA Astrophysics Data System (ADS)
Bobtsov, Alexey; Faronov, Maxim; Kolyubin, Sergey; Pyrkin, Anton
2014-12-01
The problem of simple adaptive and robust control is studied for the case of parametric and dynamic dimension uncertainties: only the maximum possible relative degree of the plant model is known. The control approach "consecutive compensator" is investigated. To illustrate the efficiency of proposed approach an example with the mobile robot motion control using computer vision system is considered.
Continuous quantum error correction as classical hybrid control
NASA Astrophysics Data System (ADS)
Mabuchi, Hideo
2009-10-01
The standard formulation of quantum error correction (QEC) comprises repeated cycles of error estimation and corrective intervention in the free dynamics of a qubit register. QEC can thus be seen as a form of feedback control, and it is of interest to seek a deeper understanding of the connection between the associated theories. Here we present a focused case study within this broad program, connecting continuous QEC with elements of hybrid control theory. We show that canonical methods of the latter engineering discipline, such as recursive filtering and dynamic programming approaches to solving the optimal control problem, can be applied fruitfully in the design of separated controller structures for quantum memories based on coding and continuous syndrome measurement.
An adaptive grid with directional control
NASA Technical Reports Server (NTRS)
Brackbill, J. U.
1993-01-01
An adaptive grid generator for adaptive node movement is here derived by combining a variational formulation of Winslow's (1981) variable-diffusion method with a directional control functional. By applying harmonic-function theory, it becomes possible to define conditions under which there exist unique solutions of the resulting elliptic equations. The results obtained for the grid generator's application to the complex problem posed by the fluid instability-driven magnetic field reconnection demonstrate one-tenth the computational cost of either a Eulerian grid or an adaptive grid without directional control.
A new adaptive configuration of PID type fuzzy logic controller.
Fereidouni, Alireza; Masoum, Mohammad A S; Moghbel, Moayed
2015-05-01
In this paper, an adaptive configuration for PID type fuzzy logic controller (FLC) is proposed to improve the performances of both conventional PID (C-PID) controller and conventional PID type FLC (C-PID-FLC). The proposed configuration is called adaptive because its output scaling factors (SFs) are dynamically tuned while the controller is functioning. The initial values of SFs are calculated based on its well-tuned counterpart while the proceeding values are generated using a proposed stochastic hybrid bacterial foraging particle swarm optimization (h-BF-PSO) algorithm. The performance of the proposed configuration is evaluated through extensive simulations for different operating conditions (changes in reference, load disturbance and noise signals). The results reveal that the proposed scheme performs significantly better over the C-PID controller and the C-PID-FLC in terms of several performance indices (integral absolute error (IAE), integral-of-time-multiplied absolute error (ITAE) and integral-of-time-multiplied squared error (ITSE)), overshoot and settling time for plants with and without dead time. PMID:25530256
Genetic algorithms in adaptive fuzzy control
NASA Technical Reports Server (NTRS)
Karr, C. Lucas; Harper, Tony R.
1992-01-01
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.
Adaptive Control for Microgravity Vibration Isolation System
NASA Technical Reports Server (NTRS)
Yang, Bong-Jun; Calise, Anthony J.; Craig, James I.; Whorton, Mark S.
2005-01-01
Most active vibration isolation systems that try to a provide quiescent acceleration environment for space science experiments have utilized linear design methods. In this paper, we address adaptive control augmentation of an existing classical controller that employs a high-gain acceleration feedback together with a low-gain position feedback to center the isolated platform. The control design feature includes parametric and dynamic uncertainties because the hardware of the isolation system is built as a payload-level isolator, and the acceleration Sensor exhibits a significant bias. A neural network is incorporated to adaptively compensate for the system uncertainties, and a high-pass filter is introduced to mitigate the effect of the measurement bias. Simulations show that the adaptive control improves the performance of the existing acceleration controller and keep the level of the isolated platform deviation to that of the existing control system.
Model-adaptive hybrid dynamic control for robotic assembly tasks
Austin, D.J.; McCarragher, B.J.
1999-10-01
A new task-level adaptive controller is presented for the hybrid dynamic control of robotic assembly tasks. Using a hybrid dynamic model of the assembly task, velocity constraints are derived from which satisfactory velocity commands are obtained. Due to modeling errors and parametric uncertainties, the velocity commands may be erroneous and may result in suboptimal performance. Task-level adaptive control schemes, based on the occurrence of discrete events, are used to change the model parameters from which the velocity commands are determined. Two adaptive schemes are presented: the first is based on intuitive reasoning about the vector spaces involved whereas the second uses a search region that is reduced with each iteration. For the first adaptation law, asymptotic convergence to the correct model parameters is proven except for one case. This weakness motivated the development of the second adaptation law, for which asymptotic convergence is proven in all cases. Automated control of a peg-in-hole assembly task is given as an example, and simulations and experiments for this task are presented. These results demonstrate the success of the method and also indicate properties for rapid convergence.
Developing control charts to review and monitor medication errors.
Ciminera, J L; Lease, M P
1992-03-01
There is a need to monitor reported medication errors in a hospital setting. Because the quantity of errors vary due to external reporting, quantifying the data is extremely difficult. Typically, these errors are reviewed using classification systems that often have wide variations in the numbers per class per month. The authors recommend the use of control charts to review historical data and to monitor future data. The procedure they have adopted is a modification of schemes using absolute (i.e., positive) values of successive differences to estimate the standard deviation when only single incidence values are available in time rather than sample averages, and when many successive differences may be zero. PMID:10116719
Controlling type-1 error rates in whole effluent toxicity testing
Smith, R.; Johnson, S.C.
1995-12-31
A form of variability, called the dose x test interaction, has been found to affect the variability of the mean differences from control in the statistical tests used to evaluate Whole Effluent Toxicity Tests for compliance purposes. Since the dose x test interaction is not included in these statistical tests, the assumed type-1 and type-2 error rates can be incorrect. The accepted type-1 error rate for these tests is 5%. Analysis of over 100 Ceriodaphnia, fathead minnow and sea urchin fertilization tests showed that when the test x dose interaction term was not included in the calculations the type-1 error rate was inflated to as high as 20%. In a compliance setting, this problem may lead to incorrect regulatory decisions. Statistical tests are proposed that properly incorporate the dose x test interaction variance.
Adaptive control of molecular alignment
Horn, C.; Wollenhaupt, M.; Krug, M.; Baumert, T.; Nalda, R. de; Banares, L.
2006-03-15
We demonstrate control on nonadiabatic molecular alignment by using a spectrally phase-shaped laser pulse. An evolutionary algorithm in a closed feedback loop has been used in order to find pulse shapes that maximize a given effect. In particular, this scheme has been applied to the optimization of total alignment, and to the control of the temporal structure of the alignment transient within a revival. Asymmetric temporal pulse shapes have been found to be very effective for the latter and have been studied separately in a single-parameter control scheme. Our experimental results are supported by numerical simulations.
Empirical versus time stepping with embedded error control for density-driven flow in porous media
NASA Astrophysics Data System (ADS)
Younes, Anis; Ackerer, Philippe
2010-08-01
Modeling density-driven flow in porous media may require very long computational time due to the nonlinear coupling between flow and transport equations. Time stepping schemes are often used to adapt the time step size in order to reduce the computational cost of the simulation. In this work, the empirical time stepping scheme which adapts the time step size according to the performance of the iterative nonlinear solver is compared to an adaptive time stepping scheme where the time step length is controlled by the temporal truncation error. Results of the simulations of the Elder problem show that (1) the empirical time stepping scheme can lead to inaccurate results even with a small convergence criterion, (2) accurate results are obtained when the time step size selection is based on the truncation error control, (3) a non iterative scheme with proper time step management can be faster and leads to more accurate solution than the standard iterative procedure with the empirical time stepping and (4) the temporal truncation error can have a significant effect on the results and can be considered as one of the reasons for the differences observed in the Elder numerical results.
Attitude-Control Algorithm for Minimizing Maneuver Execution Errors
NASA Technical Reports Server (NTRS)
Acikmese, Behcet
2008-01-01
A G-RAC attitude-control algorithm is used to minimize maneuver execution error in a spacecraft with a flexible appendage when said spacecraft must induce translational momentum by firing (in open loop) large thrusters along a desired direction for a given period of time. The controller is dynamic with two integrators and requires measurement of only the angular position and velocity of the spacecraft. The global stability of the closed-loop system is guaranteed without having access to the states describing the dynamics of the appendage and with severe saturation in the available torque. Spacecraft apply open-loop thruster firings to induce a desired translational momentum with an extended appendage. This control algorithm will assist this maneuver by stabilizing the attitude dynamics around a desired orientation, and consequently minimize the maneuver execution errors.
Optimal wavefront control for adaptive segmented mirrors
NASA Technical Reports Server (NTRS)
Downie, John D.; Goodman, Joseph W.
1989-01-01
A ground-based astronomical telescope with a segmented primary mirror will suffer image-degrading wavefront aberrations from at least two sources: (1) atmospheric turbulence and (2) segment misalignment or figure errors of the mirror itself. This paper describes the derivation of a mirror control feedback matrix that assumes the presence of both types of aberration and is optimum in the sense that it minimizes the mean-squared residual wavefront error. Assumptions of the statistical nature of the wavefront measurement errors, atmospheric phase aberrations, and segment misalignment errors are made in the process of derivation. Examples of the degree of correlation are presented for three different types of wavefront measurement data and compared to results of simple corrections.
Post-error slowing is influenced by cognitive control demand.
Regev, Shirley; Meiran, Nachshon
2014-10-01
Post-error slowing (PES) has been shown to reflect a control failure due to automatic attentional capture by the error. Here we aimed to assess whether PES also involves an increase in cognitive control. Using a cued-task-switching paradigm (Experiment 1) and a Stroop task (Experiment 2), the demand for top down control was manipulated. In Experiment 1, one group received dimension cues indicating the relevant stimulus dimension (e.g., "number") without specifying the response-category-to-key mapping, hence requiring considerable top down control. Another group was shown mapping cues providing information regarding both the relevant task identity and its category-to-key mapping (e.g., "one three"), requiring less top down control, and the last group received both types of cues, intermixed. In Experiment 2, one group performed a pure incongruent Stroop condition (name ink color of incongruent color names, high control demand), and another group received a pure neutral Stroop condition (name color patches, low control demand). In Experiment 2a, participants received the two conditions, intermixed. A larger PES was observed with dimension cues as compared with mapping cues, and with incongruent Stroop stimuli as compared to neutral stimuli, but not when the conditions were intermixed. These findings reveal that PES is influenced by the control demands that characterize the given block-wide experimental context and show that proactive cognitive control is involved in PES. PMID:25089881
An adaptive error modeling scheme for the lossless compression of EEG signals.
Sriraam, N; Eswaran, C
2008-09-01
Lossless compression of EEG signal is of great importance for the neurological diagnosis as the specialists consider the exact reconstruction of the signal as a primary requirement. This paper discusses a lossless compression scheme for EEG signals that involves a predictor and an adaptive error modeling technique. The prediction residues are arranged based on the error count through an histogram computation. Two optimal regions are identified in the histogram plot through a heuristic search such that the bit requirement for encoding the two regions is minimum. Further improvement in the compression is achieved by removing the statistical redundancy that is present in the residue signal by using a context-based bias cancellation scheme. Three neural network predictors, namely, single-layer perceptron, multilayer perceptron, and Elman network and two linear predictors, namely, autoregressive model and finite impulse response filter are considered. Experiments are conducted using EEG signals recorded under different physiological conditions and the performances of the proposed methods are evaluated in terms of the compression ratio. It is shown that the proposed adaptive error modeling schemes yield better compression results compared to other known compression methods. PMID:18779073
Adaptive Control Strategies for Flexible Robotic Arm
NASA Technical Reports Server (NTRS)
Bialasiewicz, Jan T.
1996-01-01
The control problem of a flexible robotic arm has been investigated. The control strategies that have been developed have a wide application in approaching the general control problem of flexible space structures. The following control strategies have been developed and evaluated: neural self-tuning control algorithm, neural-network-based fuzzy logic control algorithm, and adaptive pole assignment algorithm. All of the above algorithms have been tested through computer simulation. In addition, the hardware implementation of a computer control system that controls the tip position of a flexible arm clamped on a rigid hub mounted directly on the vertical shaft of a dc motor, has been developed. An adaptive pole assignment algorithm has been applied to suppress vibrations of the described physical model of flexible robotic arm and has been successfully tested using this testbed.
Using brain potentials to understand prism adaptation: the error-related negativity and the P300.
MacLean, Stephane J; Hassall, Cameron D; Ishigami, Yoko; Krigolson, Olav E; Eskes, Gail A
2015-01-01
Prism adaptation (PA) is both a perceptual-motor learning task as well as a promising rehabilitation tool for visuo-spatial neglect (VSN)-a spatial attention disorder often experienced after stroke resulting in slowed and/or inaccurate motor responses to contralesional targets. During PA, individuals are exposed to prism-induced shifts of the visual-field while performing a visuo-guided reaching task. After adaptation, with goggles removed, visuomotor responding is shifted to the opposite direction of that initially induced by the prisms. This visuomotor aftereffect has been used to study visuomotor learning and adaptation and has been applied clinically to reduce VSN severity by improving motor responding to stimuli in contralesional (usually left-sided) space. In order to optimize PA's use for VSN patients, it is important to elucidate the neural and cognitive processes that alter visuomotor function during PA. In the present study, healthy young adults underwent PA while event-related potentials (ERPs) were recorded at the termination of each reach (screen-touch), then binned according to accuracy (hit vs. miss) and phase of exposure block (early, middle, late). Results show that two ERP components were evoked by screen-touch: an error-related negativity (ERN), and a P300. The ERN was consistently evoked on miss trials during adaptation, while the P300 amplitude was largest during the early phase of adaptation for both hit and miss trials. This study provides evidence of two neural signals sensitive to visual feedback during PA that may sub-serve changes in visuomotor responding. Prior ERP research suggests that the ERN reflects an error processing system in medial-frontal cortex, while the P300 is suggested to reflect a system for context updating and learning. Future research is needed to elucidate the role of these ERP components in improving visuomotor responses among individuals with VSN. PMID:26124715
Using brain potentials to understand prism adaptation: the error-related negativity and the P300
MacLean, Stephane J.; Hassall, Cameron D.; Ishigami, Yoko; Krigolson, Olav E.; Eskes, Gail A.
2015-01-01
Prism adaptation (PA) is both a perceptual-motor learning task as well as a promising rehabilitation tool for visuo-spatial neglect (VSN)—a spatial attention disorder often experienced after stroke resulting in slowed and/or inaccurate motor responses to contralesional targets. During PA, individuals are exposed to prism-induced shifts of the visual-field while performing a visuo-guided reaching task. After adaptation, with goggles removed, visuomotor responding is shifted to the opposite direction of that initially induced by the prisms. This visuomotor aftereffect has been used to study visuomotor learning and adaptation and has been applied clinically to reduce VSN severity by improving motor responding to stimuli in contralesional (usually left-sided) space. In order to optimize PA's use for VSN patients, it is important to elucidate the neural and cognitive processes that alter visuomotor function during PA. In the present study, healthy young adults underwent PA while event-related potentials (ERPs) were recorded at the termination of each reach (screen-touch), then binned according to accuracy (hit vs. miss) and phase of exposure block (early, middle, late). Results show that two ERP components were evoked by screen-touch: an error-related negativity (ERN), and a P300. The ERN was consistently evoked on miss trials during adaptation, while the P300 amplitude was largest during the early phase of adaptation for both hit and miss trials. This study provides evidence of two neural signals sensitive to visual feedback during PA that may sub-serve changes in visuomotor responding. Prior ERP research suggests that the ERN reflects an error processing system in medial-frontal cortex, while the P300 is suggested to reflect a system for context updating and learning. Future research is needed to elucidate the role of these ERP components in improving visuomotor responses among individuals with VSN. PMID:26124715
Language control in bilinguals: The adaptive control hypothesis
Abutalebi, Jubin
2013-01-01
Speech comprehension and production are governed by control processes. We explore their nature and dynamics in bilingual speakers with a focus on speech production. Prior research indicates that individuals increase cognitive control in order to achieve a desired goal. In the adaptive control hypothesis we propose a stronger hypothesis: Language control processes themselves adapt to the recurrent demands placed on them by the interactional context. Adapting a control process means changing a parameter or parameters about the way it works (its neural capacity or efficiency) or the way it works in concert, or in cascade, with other control processes (e.g., its connectedness). We distinguish eight control processes (goal maintenance, conflict monitoring, interference suppression, salient cue detection, selective response inhibition, task disengagement, task engagement, opportunistic planning). We consider the demands on these processes imposed by three interactional contexts (single language, dual language, and dense code-switching). We predict adaptive changes in the neural regions and circuits associated with specific control processes. A dual-language context, for example, is predicted to lead to the adaptation of a circuit mediating a cascade of control processes that circumvents a control dilemma. Effective test of the adaptive control hypothesis requires behavioural and neuroimaging work that assesses language control in a range of tasks within the same individual. PMID:25077013
Language control in bilinguals: The adaptive control hypothesis.
Green, David W; Abutalebi, Jubin
2013-08-01
Speech comprehension and production are governed by control processes. We explore their nature and dynamics in bilingual speakers with a focus on speech production. Prior research indicates that individuals increase cognitive control in order to achieve a desired goal. In the adaptive control hypothesis we propose a stronger hypothesis: Language control processes themselves adapt to the recurrent demands placed on them by the interactional context. Adapting a control process means changing a parameter or parameters about the way it works (its neural capacity or efficiency) or the way it works in concert, or in cascade, with other control processes (e.g., its connectedness). We distinguish eight control processes (goal maintenance, conflict monitoring, interference suppression, salient cue detection, selective response inhibition, task disengagement, task engagement, opportunistic planning). We consider the demands on these processes imposed by three interactional contexts (single language, dual language, and dense code-switching). We predict adaptive changes in the neural regions and circuits associated with specific control processes. A dual-language context, for example, is predicted to lead to the adaptation of a circuit mediating a cascade of control processes that circumvents a control dilemma. Effective test of the adaptive control hypothesis requires behavioural and neuroimaging work that assesses language control in a range of tasks within the same individual. PMID:25077013
Adaptive gain control during human perceptual choice
Cheadle, Samuel; Wyart, Valentin; Tsetsos, Konstantinos; Myers, Nicholas; de Gardelle, Vincent; Castañón, Santiago Herce; Summerfield, Christopher
2015-01-01
Neural systems adapt to background levels of stimulation. Adaptive gain control has been extensively studied in sensory systems, but overlooked in decision-theoretic models. Here, we describe evidence for adaptive gain control during the serial integration of decision-relevant information. Human observers judged the average information provided by a rapid stream of visual events (samples). The impact that each sample wielded over choices depended on its consistency with the previous sample, with more consistent or expected samples wielding the greatest influence over choice. This bias was also visible in the encoding of decision information in pupillometric signals, and in cortical responses measured with functional neuroimaging. These data can be accounted for with a new serial sampling model in which the gain of information processing adapts rapidly to reflect the average of the available evidence. PMID:24656259
Adaptive output feedback control of flexible systems
NASA Astrophysics Data System (ADS)
Yang, Bong-Jun
Neural network-based adaptive output feedback approaches that augment a linear control design are described in this thesis, and emphasis is placed on their real-time implementation with flexible systems. Two different control architectures that are robust to parametric uncertainties and unmodelled dynamics are presented. The unmodelled effects can consist of minimum phase internal dynamics of the system together with external disturbance process. Within this context, adaptive compensation for external disturbances is addressed. In the first approach, internal model-following control, adaptive elements are designed using feedback inversion. The effect of an actuator limit is treated using control hedging, and the effect of other actuation nonlinearities, such as dead zone and backlash, is mitigated by a disturbance observer-based control design. The effectiveness of the approach is illustrated through simulation and experimental testing with a three-disk torsional system, which is subjected to control voltage limit and stiction. While the internal model-following control is limited to minimum phase systems, the second approach, external model-following control, does not involve feedback linearization and can be applied to non-minimum phase systems. The unstable zero dynamics are assumed to have been modelled in the design of the existing linear controller. The laboratory tests for this method include a three-disk torsional pendulum, an inverted pendulum, and a flexible-base robot manipulator. The external model-following control architecture is further extended in three ways. The first extension is an approach for control of multivariable nonlinear systems. The second extension is a decentralized adaptive control approach for large-scale interconnected systems. The third extension is to make use of an adaptive observer to augment a linear observer-based controller. In this extension, augmenting terms for the adaptive observer can be used to achieve adaptation in
Adaptive Modal Identification for Flutter Suppression Control
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Drew, Michael; Swei, Sean S.
2016-01-01
In this paper, we will develop an adaptive modal identification method for identifying the frequencies and damping of a flutter mode based on model-reference adaptive control (MRAC) and least-squares methods. The least-squares parameter estimation will achieve parameter convergence in the presence of persistent excitation whereas the MRAC parameter estimation does not guarantee parameter convergence. Two adaptive flutter suppression control approaches are developed: one based on MRAC and the other based on the least-squares method. The MRAC flutter suppression control is designed as an integral part of the parameter estimation where the feedback signal is used to estimate the modal information. On the other hand, the separation principle of control and estimation is applied to the least-squares method. The least-squares modal identification is used to perform parameter estimation.
Dual adaptive control: Design principles and applications
NASA Technical Reports Server (NTRS)
Mookerjee, Purusottam
1988-01-01
The design of an actively adaptive dual controller based on an approximation of the stochastic dynamic programming equation for a multi-step horizon is presented. A dual controller that can enhance identification of the system while controlling it at the same time is derived for multi-dimensional problems. This dual controller uses sensitivity functions of the expected future cost with respect to the parameter uncertainties. A passively adaptive cautious controller and the actively adaptive dual controller are examined. In many instances, the cautious controller is seen to turn off while the latter avoids the turn-off of the control and the slow convergence of the parameter estimates, characteristic of the cautious controller. The algorithms have been applied to a multi-variable static model which represents a simplified linear version of the relationship between the vibration output and the higher harmonic control input for a helicopter. Monte Carlo comparisons based on parametric and nonparametric statistical analysis indicate the superiority of the dual controller over the baseline controller.
Goffin, Mark A.; Baker, Christopher M.J.; Buchan, Andrew G.; Pain, Christopher C.; Eaton, Matthew D.; Smith, Paul N.
2013-06-01
This article presents a method for goal-based anisotropic adaptive methods for the finite element method applied to the Boltzmann transport equation. The neutron multiplication factor, k{sub eff}, is used as the goal of the adaptive procedure. The anisotropic adaptive algorithm requires error measures for k{sub eff} with directional dependence. General error estimators are derived for any given functional of the flux and applied to k{sub eff} to acquire the driving force for the adaptive procedure. The error estimators require the solution of an appropriately formed dual equation. Forward and dual error indicators are calculated by weighting the Hessian of each solution with the dual and forward residual respectively. The Hessian is used as an approximation of the interpolation error in the solution which gives rise to the directional dependence. The two indicators are combined to form a single error metric that is used to adapt the finite element mesh. The residual is approximated using a novel technique arising from the sub-grid scale finite element discretisation. Two adaptive routes are demonstrated: (i) a single mesh is used to solve all energy groups, and (ii) a different mesh is used to solve each energy group. The second method aims to capture the benefit from representing the flux from each energy group on a specifically optimised mesh. The k{sub eff} goal-based adaptive method was applied to three examples which illustrate the superior accuracy in criticality problems that can be obtained.
Errors in paleomagnetism: Structural control on overlapped vectors - mathematical models
NASA Astrophysics Data System (ADS)
Rodríguez-Pintó, A.; Ramón, M. J.; Oliva-Urcia, B.; Pueyo, E. L.; Pocoví, A.
2011-05-01
The reliability of paleomagnetic data is a keystone to obtain trustable kinematics interpretations. The determination of the real paleomagnetic component recorded at certain time in the geological evolution of a rock can be affected by several sources of errors: inclination shallowing, declination biases caused by incorrect restoration to the ancient field, internal deformation of rock volumes and lack of isolation of the paleomagnetic primary vector during the laboratory procedures (overlapping of components). These errors will limit or impede the validity of paleomagnetism as the only three-dimension reference. This paper presents the first systematic modeling of the effect of overlapped vectors referred to declination, inclination and stability tests taking into account the key variables: orientation of a primary and secondary (overlapped to the primary) vectors, degree of overlapping (intensity ratio of primary and secondary paleomagnetic vectors) and the fold axis orientation and dip of bedding plane. In this way, several scenarios of overlapping have been modeled in different fold geometries considering both polarities and all the variables aforementioned, allowing to calculate the deviations of the vector obtained in the laboratory (overlapped) with respect to the paleomagnetic reference (not overlapped). Observations from the models confirm that declination errors are larger than the inclination ones. In addition to the geometry factor, errors are mainly controlled by the relative magnitude of the primary respect to the secondary component (P/S ratio). We observe larger asymmetries and bigger magnitudes of errors along the fold location if the primary and secondary records have different polarities. If the primary record (declination) and the fold axis orientation are perpendicular ( Ω = 90°), errors reach maximum magnitudes and larger asymmetries along the fold surface (different dips). The effect of overlapping in the fold and reversal tests is also
Human error model adaptation and validation for Savannah River Site nonreactor facilities
Eide, S.A.; Benhardt, H.C.; Held, J.E.; Olsen, L.M.; Vail, R.E.
1993-09-01
As part of an overall effort to improve safety analysis methods for the Savannah River Site (SRS) nonreactor nuclear facilities, a comprehensive human reliability analysis (HRA) methodology has been developed and selectively validated. The HRA methodology covers a wide variety of human errors that may exist in risk analyses of the nonreactor nuclear facilities. Such risk analyses are an integral part of safety analysis reports (SARS) at the SRS, forming the basis for severe accident analysis and assisting in the identification of safety classes for equipment. Nonreactor nuclear facilities at the SRS include nuclear fuel fabrication and reprocessing, nuclear waste processing, and nuclear waste storage and disposal. The SRS HRA methodology improvement included both adaptation of existing human error models and validation of selected model results with SRS-specific data on actual human errors. The data were obtained from three existing SRS data bases: (1) Fuel Processing, (2) Fuel Fabrication, and (3) Waste Management. These three are part of the Risk Analysis Methodology (RAM) Fault Tree data banks. Events in these data banks are obtained from a wide variety of sources, including operator log books, occurrence reports, safety newsletters, and others. Validation of the human error models involved comparison with SRS-specific data and calibration of model results where appropriate.
High speed and adaptable error correction for megabit/s rate quantum key distribution
Dixon, A. R.; Sato, H.
2014-01-01
Quantum Key Distribution is moving from its theoretical foundation of unconditional security to rapidly approaching real world installations. A significant part of this move is the orders of magnitude increases in the rate at which secure key bits are distributed. However, these advances have mostly been confined to the physical hardware stage of QKD, with software post-processing often being unable to support the high raw bit rates. In a complete implementation this leads to a bottleneck limiting the final secure key rate of the system unnecessarily. Here we report details of equally high rate error correction which is further adaptable to maximise the secure key rate under a range of different operating conditions. The error correction is implemented both in CPU and GPU using a bi-directional LDPC approach and can provide 90–94% of the ideal secure key rate over all fibre distances from 0–80 km. PMID:25450416
High speed and adaptable error correction for megabit/s rate quantum key distribution
NASA Astrophysics Data System (ADS)
Dixon, A. R.; Sato, H.
2014-12-01
Quantum Key Distribution is moving from its theoretical foundation of unconditional security to rapidly approaching real world installations. A significant part of this move is the orders of magnitude increases in the rate at which secure key bits are distributed. However, these advances have mostly been confined to the physical hardware stage of QKD, with software post-processing often being unable to support the high raw bit rates. In a complete implementation this leads to a bottleneck limiting the final secure key rate of the system unnecessarily. Here we report details of equally high rate error correction which is further adaptable to maximise the secure key rate under a range of different operating conditions. The error correction is implemented both in CPU and GPU using a bi-directional LDPC approach and can provide 90-94% of the ideal secure key rate over all fibre distances from 0-80 km.
Optimal and adaptive control in canine postural regulation.
Schuster, D; Talbott, R E
1980-07-01
For analytic purposes, dogs trained to stand quietly on an oscillating platform can be likened to a fixed-length inverted pendulum with a point mass. Describing function analysis permitted derivation of torque and error values as functions of phase and gain relative to platform movement. A phase criterion was determined for minimization of either control torque at a given error amplitude or error at a given control torque amplitude. Describing functions for dogs with and without vision approached optimal phase. Stretch reflex control involving proportional-plus-rate feedback is not sufficient to account for the approach to optimal phase. Blindfolded labyrinthectomized dogs did not exhibit optimal behavior and the phase constraint for stretch reflex control was satisfied at most frequencies. The observed behavior is best accounted for by a model involving both otolith and visual feedforward (pursuit-precognitive) control processes. Reductions in phase lag by blindfolded dogs during the first few cycles of platform motion provide evidence of adaptive control. PMID:7396044
Coordinated joint motion control system with position error correction
Danko, George L.
2016-04-05
Disclosed are an articulated hydraulic machine supporting, control system and control method for same. The articulated hydraulic machine has an end effector for performing useful work. The control system is capable of controlling the end effector for automated movement along a preselected trajectory. The control system has a position error correction system to correct discrepancies between an actual end effector trajectory and a desired end effector trajectory. The correction system can employ one or more absolute position signals provided by one or more acceleration sensors supported by one or more movable machine elements. Good trajectory positioning and repeatability can be obtained. A two joystick controller system is enabled, which can in some cases facilitate the operator's task and enhance their work quality and productivity.
Coordinated joint motion control system with position error correction
Danko, George
2011-11-22
Disclosed are an articulated hydraulic machine supporting, control system and control method for same. The articulated hydraulic machine has an end effector for performing useful work. The control system is capable of controlling the end effector for automated movement along a preselected trajectory. The control system has a position error correction system to correct discrepancies between an actual end effector trajectory and a desired end effector trajectory. The correction system can employ one or more absolute position signals provided by one or more acceleration sensors supported by one or more movable machine elements. Good trajectory positioning and repeatability can be obtained. A two-joystick controller system is enabled, which can in some cases facilitate the operator's task and enhance their work quality and productivity.
An adaptive robust controller for time delay maglev transportation systems
NASA Astrophysics Data System (ADS)
Milani, Reza Hamidi; Zarabadipour, Hassan; Shahnazi, Reza
2012-12-01
For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov-Krasovskii synthesis method, therefore asymptotic stability is guaranteed.
Error control techniques for satellite and space communications
NASA Technical Reports Server (NTRS)
Costello, Daniel J., Jr.
1991-01-01
Research activities related to error control techniques for satellite and space communication are reported. Specific areas of research include: coding gains for bandwidth efficient codes, hardware implementation of a bandwidth efficient coding scheme for the Hubble Space Telescope, construction of long trellis codes for use with sequential decoding, performance analysis of multilevel trellis codes, and M-algorithm decoding of trellis codes. Each topic is discussed in a corresponding paper that appears in the appendices.
Error message recording and reporting in the SLC control system
Spencer, N.; Bogart, J.; Phinney, N.; Thompson, K.
1985-04-01
Error or information messages that are signaled by control software either in the VAX host computer or the local microprocessor clusters are handled by a dedicated VAX process (PARANOIA). Messages are recorded on disk for further analysis and displayed at the appropriate console. Another VAX process (ERRLOG) can be used to sort, list and histogram various categories of messages. The functions performed by these processes and the algorithms used are discussed.
Adaptive neural control of aeroelastic response
NASA Astrophysics Data System (ADS)
Lichtenwalner, Peter F.; Little, Gerald R.; Scott, Robert C.
1996-05-01
The Adaptive Neural Control of Aeroelastic Response (ANCAR) program is a joint research and development effort conducted by McDonnell Douglas Aerospace (MDA) and the National Aeronautics and Space Administration, Langley Research Center (NASA LaRC) under a Memorandum of Agreement (MOA). The purpose of the MOA is to cooperatively develop the smart structure technologies necessary for alleviating undesirable vibration and aeroelastic response associated with highly flexible structures. Adaptive control can reduce aeroelastic response associated with buffet and atmospheric turbulence, it can increase flutter margins, and it may be able to reduce response associated with nonlinear phenomenon like limit cycle oscillations. By reducing vibration levels and loads, aircraft structures can have lower acquisition cost, reduced maintenance, and extended lifetimes. Phase I of the ANCAR program involved development and demonstration of a neural network-based semi-adaptive flutter suppression system which used a neural network for scheduling control laws as a function of Mach number and dynamic pressure. This controller was tested along with a robust fixed-gain control law in NASA's Transonic Dynamics Tunnel (TDT) utilizing the Benchmark Active Controls Testing (BACT) wing. During Phase II, a fully adaptive on-line learning neural network control system has been developed for flutter suppression which will be tested in 1996. This paper presents the results of Phase I testing as well as the development progress of Phase II.
Robust Transmission of H.264/AVC Streams Using Adaptive Group Slicing and Unequal Error Protection
NASA Astrophysics Data System (ADS)
Thomos, Nikolaos; Argyropoulos, Savvas; Boulgouris, Nikolaos V.; Strintzis, Michael G.
2006-12-01
We present a novel scheme for the transmission of H.264/AVC video streams over lossy packet networks. The proposed scheme exploits the error-resilient features of H.264/AVC codec and employs Reed-Solomon codes to protect effectively the streams. A novel technique for adaptive classification of macroblocks into three slice groups is also proposed. The optimal classification of macroblocks and the optimal channel rate allocation are achieved by iterating two interdependent steps. Dynamic programming techniques are used for the channel rate allocation process in order to reduce complexity. Simulations clearly demonstrate the superiority of the proposed method over other recent algorithms for transmission of H.264/AVC streams.
Neuronal Control of Adaptive Thermogenesis
Yang, Xiaoyong; Ruan, Hai-Bin
2015-01-01
The obesity epidemic continues rising as a global health challenge, despite the increasing public awareness and the use of lifestyle and medical interventions. The biomedical community is urged to develop new treatments to obesity. Excess energy is stored as fat in white adipose tissue (WAT), dysfunction of which lies at the core of obesity and associated metabolic disorders. By contrast, brown adipose tissue (BAT) burns fat and dissipates chemical energy as heat. The development and activation of “brown-like” adipocytes, also known as beige cells, result in WAT browning and thermogenesis. The recent discovery of brown and beige adipocytes in adult humans has sparked the exploration of the development, regulation, and function of these thermogenic adipocytes. The central nervous system drives the sympathetic nerve activity in BAT and WAT to control heat production and energy homeostasis. This review provides an overview of the integration of thermal, hormonal, and nutritional information on hypothalamic circuits in thermoregulation. PMID:26441839
Inhibitory control and error monitoring by human subthalamic neurons
Bastin, J; Polosan, M; Benis, D; Goetz, L; Bhattacharjee, M; Piallat, B; Krainik, A; Bougerol, T; Chabardès, S; David, O
2014-01-01
The subthalamic nucleus (STN) has been shown to be implicated in the control of voluntary action, especially during tasks involving conflicting choice alternatives or rapid response suppression. However, the precise role of the STN during nonmotor functions remains controversial. First, we tested whether functionally distinct neuronal populations support different executive control functions (such as inhibitory control or error monitoring) even within a single subterritory of the STN. We used microelectrode recordings during deep brain stimulation surgery to study extracellular activity of the putative associative-limbic part of the STN while patients with severe obsessive-compulsive disorder performed a stop-signal task. Second, 2–4 days after the surgery, local field potential recordings of STN were used to test the hypothesis that STN oscillations may also reflect executive control signals. Extracellular recordings revealed three functionally distinct neuronal populations: the first one fired selectively before and during motor responses, the second one selectively increased their firing rate during successful inhibitory control, and the last one fired selectively during error monitoring. Furthermore, we found that beta band activity (15–35 Hz) rapidly increased during correct and incorrect behavioral stopping. Taken together, our results provide critical electrophysiological support for the hypothesized role of the STN in the integration of motor and cognitive-executive control functions. PMID:25203170
NASA Astrophysics Data System (ADS)
Wu, Zhenhui; Dong, Chaoyang
2006-11-01
Because of nonlinearity and strong coupling of reaction-jet and aerodynamics compound control missile, a missile autopilot design method based on adaptive fuzzy sliding mode control (AFSMC) is proposed in this paper. The universal approximation ability of adaptive fuzzy system is used to approximate the nonlinear function in missile dynamics equation during the flight of high angle of attack. And because the sliding mode control is robustness to external disturbance strongly, the sliding mode surface of the error system is constructed to overcome the influence of approximation error and external disturbance so that the actual overload can track the maneuvering command with high precision. Simulation results show that the missile autopilot designed in this paper not only can track large overload command with higher precision than traditional method, but also is robust to model uncertainty and external disturbance strongly.